Color conversion device and method

ABSTRACT

A color conversion device and method are provided in which six hues and inter-hue areas are corrected independently, and the conversion characteristics can be changed flexibly, and which does not require a large-capacity memory. Coefficients of second-order and first-order calculation terms relating to the respective hues, first-order calculation term using comparison-result data relating to the respective inter-hue areas, and product terms based on the comparison-result data and the hue data are changed so as to change the target hue or inter-hue area, without influencing other hues or inter-hue areas.

This application claims priority under 35 U.S.C. §120 of priorapplication Ser. No. 09/349,946 filed on Jul. 8, 1999 now U.S. Pat. No.6,766,049, which is a continuation of application Ser. No. 09/312,712filed on May 17, 1999 (now U.S. Pat. No. 6,125,202), which is adivisional application of application Ser. No. 08/925,082 filed on Sep.8, 1997 (now U.S. Pat. No. 5,917,959), which is a divisional applicationof application Ser. No. 08/667,931 filed on Jun. 24, 1996 (now U.S. Pat.No. 5,729,636), which is a divisional application of application Ser.No. 08/600,204 filed on Feb. 12, 1996 (now U.S. Pat. No. 5,588,050),which is a continuation of application Ser. No. 08/292,012 filed on Aug.18, 1994, which was abandoned.

BACKGROUND OF THE INVENTION

The present invention relates to data processing used for a full-colorprinting related equipment such as a printer, a video printer, or ascanner, an image processor for forming computer graphic images or adisplay device such as a monitor. More specifically, the inventionrelates to a color conversion device and a color conversion method forperforming color conversion for image data of three colors of red, greenand blue in accordance with the equipment used.

Color conversion in printing is an indispensable technology forcompensating deterioration of image quality due to color mixing propertydue to the fact that the ink is not of a pure color, or thenon-linearity (in the hue) of the image-printing, in order to output aprinted image with a high color reproducibility. Also, in a displaydevice such as a monitor or the like, color conversion is performed inorder to output (display) an image having desired color reproducibilityin accordance with conditions under which the device is used or the likewhen an inputted color signal is to be displayed.

Conventionally, two methods have been available for the foregoing colorconversion: a table conversion method and a matrix calculation method.

In the table conversion method, image data of red, green and blue(referred to “R, G and B”, hereinafter) are inputted to obtain imagedata of R, G and B stored beforehand in a memory such as ROM orcomplementary color data of yellow, magenta and cyan (referred to as “Y,M and C”, hereinafter). Since an arbitrary conversion characteristic canbe employed, this table conversion method has an advantageous in thatcolor conversion can be effected with good color reproducibility.

However, in a simple structure for storing data for each combination ofimage data, a large-capacity memory of about 400 Mbit must be used. Forexample, even in the case of a compression method for memory capacitydisclosed in Japanese Patent Kokai Publication No. S63-227181, memorycapacity is about 5 Mbit. Therefore, a problem inherent in the tableconversion system is that since a large-capacity memory is necessary foreach conversion characteristic, it is difficult to implement the methodby means of an LSI, and it is also impossible to deal with changes inthe condition under which the conversion is carried out.

On the other hand, in the case of the matrix calculation method, forexample, for obtaining printing data of Y, M and C from image data of R,G and B, the following formula (42) is used as a basic calculationformula. $\begin{matrix}{\begin{bmatrix}Y \\M \\C\end{bmatrix} = {({Aij})\begin{bmatrix}R \\G \\B\end{bmatrix}}} & (42)\end{matrix}$

Here, i=1 to 3, and j=1 to 3.

However, by the simple linear calculation of the formula (42), it isimpossible to provide a good conversion characteristic because of anon-linearity of an image-printing or the like.

A method has been proposed for providing a conversion characteristic toimprove the foregoing characteristic. This method is disclosed inJapanese Patent Application Kokoku Publication H2-30226, directed to“color correction calculation device, and employs a matrix calculationformula (43) below. $\begin{matrix}{\begin{bmatrix}Y \\M \\C\end{bmatrix} = {({Dij})\begin{bmatrix}{R\quad} \\{G\quad} \\{B\quad} \\{R*G} \\{G*B} \\{B*R} \\{R*R} \\{G*G} \\{B*B} \\{N\quad}\end{bmatrix}}} & (43)\end{matrix}$

Here, N is a constant, i=1 to 3, and j=1 to 10.

In the foregoing formula (43), since image data having a mixture of anachromatic component and a color component is directly used, mutualinterference occur in computation. In other words, if one of thecoefficients is changed, influence is given to the components or huesother than the target component or hue (the component or hue for whichthe coefficient is changed). Consequently, a good conversioncharacteristic cannot be realized.

A color conversion method disclosed in Japanese Patent Application KokaiPublication H7-170404 is a proposed solution to this problem. FIG. 39 isa block circuit diagram showing the color conversion method forconversion of image data of R, G and B into printing data of C, M and Y,disclosed in Japanese Patent Application Kokai Publication H5-260943. Areference numeral 100 denotes a complement calculator; 101, a minimumand maximum calculator; 102, a hue data calculator; 103, a polynomialcalculator; 104, a matrix calculator; 105, a coefficient generator; and106, a synthesizer.

Next, the operation will be described. The complement calculator 100receives image data R, G and B, and outputs complementary color data Ci,Mi and Yi which have been obtained by determining 1's complements. Theminimum and maximum calculator 101 outputs a maximum value β and aminimum value α of this complementary color data and an identificationcode S for indicating, among the six hue data, data which are zero.

The hue data calculator 102 receives the complementary color data Ci, Miand Yi and the maximum and minimum values β and α, and outputs six huedata r, g, b, y, m and c which are obtained by executing the followingsubtraction: r=β−Ci, g=β−Mi, b=β−Yi, y=Yi−α, m=Mi−α, and c=Ci−α. Here,among the six hue data, at least two are of a value “zero.”

The polynomial calculator 103 receives the hue data and theidentification code S, selects, from r, g and b, two data Q1 and Q2which are not zero and, from y, m and c, two data P1 and P2 which arenot zero. Based on these data, the polynomial calculator 103 computespolynomial data: T1=P1*P2, T3=Q1*Q2, T2=T1/(P1+P2), and T4=T3/(Q1+Q2),and then outputs the results of the calculation.

The coefficient generator 105 generates calculation coefficients U(Fij)and fixed coefficients U(Fij) for the polynomial data based oninformation regarding the identification code S. The matrix calculator104 receives the hue data y, m and c, the polynomial data T1 to T4 andthe coefficients U, and outputs a result of the following formula (44)as color ink data C1, M1 and Y1. $\begin{matrix}{\begin{bmatrix}{C1} \\{M1} \\{Y1}\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{{c*m}\quad} \\{{m*y}\quad} \\{{y*c}\quad} \\{{r*g}\quad} \\{{g*b}\quad} \\{{b*r}\quad} \\\begin{matrix}{c*{m/\left( {c + m} \right)}} \\{m*{y/\left( {m + y} \right)}} \\{y*{c/\left( {y + c} \right)}} \\{r*{g/\left( {r + g} \right)}} \\{g*{b/\left( {g + b} \right)}} \\{b*{r/\left( {b + r} \right)}}\end{matrix}\end{bmatrix}}}} & (44)\end{matrix}$

The synthesizer 106 adds together the color ink data C1, M1 and Y1 anddata α which is the achromatic data, and outputs printing data C, M andY. Accordingly, the following formula (45) is used for obtainingprinting data. $\begin{matrix}{\begin{bmatrix}C \\M \\Y\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{{c*m}\quad} \\{{m*y}\quad} \\{{y*c}\quad} \\{{r*g}\quad} \\{{g*b}\quad} \\{{b*r}\quad} \\\begin{matrix}{c*{m/\left( {c + m} \right)}} \\{m*{y/\left( {m + y} \right)}} \\{y*{c/\left( {y + c} \right)}} \\{r*{g/\left( {r + g} \right)}} \\{g*{b/\left( {g + b} \right)}} \\{b*{r/\left( {b + r} \right)}}\end{matrix}\end{bmatrix}} + \begin{bmatrix}\alpha \\\alpha \\\alpha\end{bmatrix}}} & (45)\end{matrix}$

The formula (45) is a general formula for a group of pixels.

FIGS. 40A to 40F, which are schematic diagrams, show relations betweensix hues of red (R), green (G), blue (B), yellow (Y), cyan (C) andmagenta (M) and hue data y, m, c, r, g and b, and each hue data relatesto or extends to cover three hues.

FIGS. 41A to 41F, which are schematic diagrams, show relations betweenthe six hues and product terms m*y, r*g, y*c, g*b, c*m and b*r, and itis seen that each hue data relates to specified hue among the six hues.

Thus, each of the six product terms m*y, c*m, y*c, r*g, g*b and b*rrelates to only one specific hue among the six hues of red, blue, green,yellow, cyan and magenta. In other words, only m*y is an effectiveproduct term for red; c*m for blue; y*c for green; r*g for yellow; g*bfor cyan; and b*r for magenta.

Also, each of the six fraction terms m*y/(m+y), c*m/(c+m), y*c/(y+c),r*g/(r+g), g*b/(g+b) and b*r/(b+r) in the formula (45) relates to onlyone specific hue among the six hues.

As apparent from the foregoing, according to the color conversion methodshown in FIG. 39, by changing coefficients for the product terms and thefraction terms regarding the specific hue, only the target hue can beadjusted without influencing other hues.

Each of the foregoing product terms is determined by a second-ordercomputation for chroma, and each of the fraction terms is determined bya first-order computation for chroma. Thus, by using both of the productterms and the fraction terms, the non-linearity of an image-printing forchroma can be corrected.

However, even in this color conversion method, the problems of thenon-linearity of image-printing for hues remains to be solved. If anarea in a color space occupied by specific hues is to be expanded orreduced, according to the user's preference, e.g., specifically, ifexpansion or reduction of an area of red in a color space includingmagenta, red and yellow is desired, the conventional color conversionmethod of the matrix computation type could not meet with such a desire.

The problems of the conventional color conversion method or colorconversion device are summarized as follows. Where the color conversiondevice is of a table conversion method employing a memory such as ROM, alarge-capacity memory is required, and a conversion characteristiccannot be flexibly changed. Where the color conversion device uses amatrix calculation method, although it is possible to change only atarget hue, it is not possible to correct the inter-hue area betweenadjacent ones of the six hues of red, blue, green, yellow, cyan andmagenta, good conversion characteristics cannot be realized throughoutthe entire color space.

SUMMARY OF THE INVENTION

The invention has been made to overcome the problems described above,and its object is to provide a color conversion device and a colorconversion method with which it is possible to adjust the six hues ofred, blue, green, yellow, cyan and magenta, and the six inter-hue areas,with which the conversion characteristics can be flexibly varied, andwhich does not require a large-capacity memory.

According to a first aspect of the invention, there is provided a colorconversion device comprising:

calculating means for calculating maximum and minimum values β and α ofimage information for each pixel;

hue data calculating means for calculating hue data, r, g, b, y, m and cbased on the image information, and the maximum and minimum values β andα outputted from said calculating means;

means for generating comparison-result data based on said hue dataoutputted from said hue data calculating means;

first calculating means for performing calculation on outputs from saidcomparison-result data generating means and said hue data outputted fromsaid hue data calculating means;

second calculating means for performing calculation on said hue dataoutputted from said hue data calculating means;

coefficient generating means for generating predetermined matrixcoefficients; and

means for performing matrix calculation using the comparison-result datafrom said comparison-result data generating means, outputs from saidfirst and second calculating means, the hue data from said hue datacalculating means, the minimum value α from said calculating means andthe coefficients from said coefficient generating means, to therebyobtain color-converted image information.

With the above arrangement, it is possible to independently correct, inaddition to the six hues of red, blue, green, yellow, cyan and magenta,the six inter-hue areas of red-yellow, yellow-green, green-cyan,cyan-blue, blue-magenta, and magenta-red.

It is also possible to flexibly change the conversion characteristics,and the large-capacity memory is not required.

It may be so arranged that

said calculating means for calculating said maximum and minimum values βand α includes means for calculating maximum and minimum values β and αof image data R, G and B which is image information for each pixel,

said hue data calculating means includes means for calculating hue data,r, g, b, y, m and c by performing subtraction:r=R−α,g=G−α,b=B−α,y=β−B,m=β−G, andc=β−R,on said image data R, G and B and said maximum and minimum values β andα outputted from said calculating means,

said comparison-result data generating means includes:

multiplying means for multiplying said hue data by predeterminedcalculation coefficients aq1 to aq6 and ap1 to ap6,

first comparison-result data generating means for obtainingcomparison-result datahry=min(aq1*g, and ap1*m),hrm=min(aq2*b, and ap2*y),hgy=min(aq3*r, and ap3*c),hgc=min(aq4*b, and ap4*y),hbm=min(aq5*r, and ap5*c), andhbc=min(aq6*g, and ap6*m),(where min(A, B) represent minimum values of A and B), betweenrespective outputs from said multiplying means, and

second comparison-result data generating means for obtainingcomparison-result data between said comparison-result data outputtedfrom said first comparison-result data generating means and said huedata,

said first calculating means includes means for obtaining product termsbased on said outputs from said first comparison-result data generatingmeans and said hue data,

said second calculating means includes means for obtaining product termsand fraction terms on said hue data, and

said matrix calculation means performs matrix calculation using thecomparison-result data from said comparison-result data generatingmeans, the outputs from said first and second calculating means, the huedata from said hue data calculating means and the minimum value α fromsaid calculating means, to obtain the color-converted image data.

It may be so arranged that

said calculating means for calculating said maximum and minimum values βand α includes means for calculating maximum and minimum values β and αof complementary color data C, M and Y of cyan, magenta and yellow whichis image information for each pixel,

said hue data calculating means includes means for calculating hue datar, g, b, y, m and c by performing subtraction:r=β−C,g=β−M,b=β−Y,y=Y−α,m=M−α, andc=C−α,on said complementary color data C, M and Y and said maximum and minimumvalues β and α outputted from said calculating means,

said comparison-result data generating means includes:

multiplying means for multiplying said hue data by predeterminedcalculation coefficients aq1 to aq6 and ap1 to ap6,

first comparison-result data generating means for obtainingcomparison-result datahry=min(aq1*g, and ap1*m),hrm=min(aq2*b, and ap2*y),hgy=min(aq3*r, and ap3*c),hgc=min(aq4*b, and ap4*y),hbm=min(aq5*r, and ap5*c), andhbc=min(aq6*g, and ap6*m),(where min(A, B) represent minimum values of A and B), betweenrespective outputs from said multiplying means, and

second comparison-result data generating means for obtainingcomparison-result data between said comparison-result data outputtedfrom said first comparison-result data generating means and said huedata,

said first calculating means includes means for obtaining product termsbased on said outputs from said first comparison-result data generatingmeans and said hue data,

said second calculating means includes means for obtaining product termsand fraction terms on said hue data, and

said matrix calculation means performs matrix calculation using thecomparison-result data from said comparison-result data generatingmeans, the outputs from said first and second calculating means, the huedata from said hue data calculating means and the minimum value α fromsaid calculating means, to obtain the color-converted image data.

It may be so arranged that

said calculating means for calculating said maximum and minimum values βand α includes means for calculating maximum and minimum values β and αof image data R, G and B which is image information for each pixel,

said hue data calculating means includes means for calculating hue data,r, g, b, y, m and c by performing subtraction:r=R−α,g=G−α,b=B−α,y=β−B,m=β−G, andc=β−R,on said image data R, G and B and said maximum and minimum values β andα outputted from said calculating means,

said comparison-result data generating means includes:

multiplying means for multiplying said hue data by predeterminedcalculation coefficients aq1 to aq6 and ap1 to ap6,

first comparison-result data generating means for obtainingcomparison-result datahry=min(aq1*g, and ap1*m),hrm=min(aq2*b, and ap2*y),hgy=min(aq3*r, and ap3*c),hgc=min(aq4*b, and ap4*y),hbm=min(aq5*r, and ap5*c), andhbc=min(aq6*g, and ap6*m),(where min(A, B) represent minimum values of A and B), betweenrespective outputs from said multiplying means, and

second comparison-result data generating means for obtainingcomparison-result data between said comparison-result data outputtedfrom said first comparison-result data generating means and said huedata,

means for determining comparison-result data between the hue data r, gand b, and between the hue data y, m and c;

said first calculating means includes means for obtaining product termsbased on said outputs from said first comparison-result data generatingmeans and said hue data,

said second calculating means includes means for obtaining product termson said hue data, and

said matrix calculation means performs matrix calculation using thecomparison-result data from said comparison-result data generatingmeans, the outputs from said first and second calculating means, the huedata from said hue data calculating means and the minimum value α fromsaid calculating means, to obtain the color-converted image data.

It may be so arranged that

said calculating means for calculating said maximum and minimum values βand α includes means for calculating maximum and minimum values β and αof complementary color data C, M and Y which is image information foreach pixel,

said hue data calculating means includes means for calculating hue data,r, g, b, y, m and c by performing subtraction:r=β−C,g=β−M,b=β−Y,y=Y−α,m=M−α, andc=C−α,on said complementary color data C, M and Y and said maximum and minimumvalues β and α outputted from said calculating means,

said comparison-result data generating means includes:

multiplying means for multiplying said hue data by predeterminedcalculation coefficients aq1 to aq6 and ap1 to ap6,

first comparison-result data generating means for obtainingcomparison-result datahry=min(aq1*g, and ap1*m),hrm=min(aq2*b, and ap2*y),hgy=min(aq3*r, and ap3*c),hgc=min(aq4*b, and ap4*y),hbm=min(aq5*r, and ap5*c), andhbc=min(aq6*g, and ap6*m),(where min(A, B) represent minimum values of A and B), betweenrespective outputs from said multiplying means, and

second comparison-result data generating means for obtainingcomparison-result data between said comparison-result data outputtedfrom said first comparison-result data generating means and said huedata,

means for determining comparison-result data between the hue data r, gand b, and between the hue data y, m and c;

said first calculating means includes means for obtaining product termsbased on said outputs from said first comparison-result data generatingmeans and said hue data,

said second calculating means includes means for obtaining product termson said hue data, and

said matrix calculation means performs matrix calculation using thecomparison-result data from said comparison-result data generatingmeans, the outputs from said first and second calculating means, the huedata from said hue data calculating means and the minimum value α fromsaid calculating means, to obtain the color-converted image data.

It may be so arranged that

said second comparison-result data generating means obtainscomparison-result data between said comparison-result data hry, hrm,hgy, hgc, hbm and hbc and said hue data r, g and b,

said first calculating means obtains product terms between saidcomparison-result data hry, hrm, hgy, hgc, hbm and hbc outputted fromsaid first comparison-result data generating means and said hue data r,g and b,

said coefficient generating means generates predetermined matrixcoefficients Eij (i=1 to 3, and j=1 to 3) and Fij (i=1 to 3, and j=1 to25), and

said matrix calculation means performs matrix calculation of thefollowing formula (3) on said comparison-result data, said calculationterms using said comparison-result data, said calculation terms based onsaid hue data, and said minimum value α outputted from said calculatingmeans, to thereby obtain color-converted image data.

With the above arrangement, by changing the coefficients for thecalculation terms relating to the specific hue, and the first-order andsecond-order terms relating to the inter-hue areas, it is possible toadjust only the target hue or inter-hue area among the six hues of red,blue, green, yellow, cyan and magenta, and the six inter-hue areas,without influencing other hues and inter-hue areas, and by changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component withoutinfluencing the hue components.

It may be so arranged that

said second comparison-result data generating means obtainscomparison-result data between said comparison-result data hry, hrm,hgy, hgc, hbm and hbc and said hue data y, m and c,

said first calculating means obtains product terms between saidcomparison-result data hry, hrm, hgy, hgc, hbm and hbc outputted fromsaid first comparison-result data generating means and said hue data y,m and c,

said coefficient generating means generates predetermined matrixcoefficient Eij (i=1 to 3, and j=1 to 3) and Fij (i=1 to 3, and j=1 to24), and

said matrix calculation means performs matrix calculation of thefollowing formula (10) on said comparison-result data, said calculationterms using said comparison-result data, said calculation terms based onsaid hue data, and said minimum value α outputted from said calculatingmeans, to thereby obtain color-converted image data.

With the above arrangement, it is possible to independently correct, inaddition to the six hues of red, blue, green, yellow, cyan and magenta,the six inter-hue areas of red-yellow, yellow-green, green-cyan,cyan-blue, blue-magenta, and magenta-red.

It is also possible to flexibly change the conversion characteristics,and the large-capacity memory is not required.

It may be so arranged that

said second comparison-result data generating means obtainscomparison-result data between said comparison-result data hry, hrm,hgy, hgc, hbm and hbc and said hue data r, g, and b,

said first calculating means obtains product terms between saidcomparison-result data hry, hrm, hgy, hgc, hbm and hbc outputted fromsaid first comparison-result data generating means and said hue data r,g and b,

said coefficient generating means generates predetermined matrixcoefficients Eij (i=1 to 3, and j=1 to 3) and Fij (i=1 to 3, and j=1 to25), and

said matrix calculation means performs matrix calculation of thefollowing formula (19) on said comparison-result data, said calculationterms using said comparison-result data, said calculation terms based onsaid hue data, and said minimum value α outputted from said calculatingmeans, to thereby obtain color-converted image data.

With the above arrangement, by changing the coefficients for thecalculation terms relating to the specific hue, and the first-order andsecond-order terms relating to the inter-hue areas, it is possible toadjust only the target hue or inter-hue area among the six hues of red,blue, green, yellow, cyan and magenta, and the six inter-hue areas,without influencing other hues and inter-hue areas, and by changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component withoutinfluencing the hue components.

It may be so arranged that

said second comparison-result data generating means obtainscomparison-result data between said comparison-result data hry, hrm,hgy, hgc, hbm and hbc and said hue data y, m and c,

said first calculating means obtains product terms between saidcomparison-result data hry, hrm, hgy, hgc, hbm and hbc outputted fromsaid first comparison-result data generating means and said hue data y,m and c,

said coefficient generating means generates predetermined matrixcoefficients Eij (i=1 to 3, and j=1 to 3) and Fij (i=1 to 3, and j=1 to25), and

said matrix calculation means performs matrix calculation of thefollowing formula (28) on said comparison-result data, said calculationterms using said comparison-result data, said calculation terms based onsaid hue data, and said minimum value α outputted from said calculatingmeans, to thereby obtain color-converted image data.

With the above arrangement, by changing the coefficients for thecalculation terms relating to the specific hue, and the first-order andsecond-order terms relating to the inter-hue areas, it is possible toadjust only the target hue or inter-hue area among the six hues of red,blue, green, yellow, cyan and magenta, and the six inter-hue areas,without influencing other hues and inter-hue areas, and by changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component withoutinfluencing the hue components.

It may be so arranged that

said coefficient generating means generates predetermined matrixcoefficients Eij (i=1 to 3, and j=1 to 3) of the following formula (33)and matrix coefficients Fij (i=1 to 3, and j=1 to 24, or j=1 to 25),each of said coefficients Fij being set to a predetermined value.$\begin{matrix}{({Eij}) = \begin{bmatrix}1 & 0 & 0 \\0 & 1 & 0 \\0 & 0 & 1\end{bmatrix}} & (33)\end{matrix}$

It may be so arranged that

said calculating means includes means for calculating the maximum andminimum values β and α of image information for each pixel andgenerating and outputting an identification code for identifying the huedata having a value zero, according to which component of the imageinformation is the maximum and minimum for each pixel,

said comparison-result data generating means generates comparison-resultdata based on said identification code outputted from said calculatingmeans,

said coefficient generating means generates matrix coefficients based onsaid identification code outputted from said calculating means, and

said matrix calculation means performs, according to said identificationcode from said calculating means, by performing matrix calculation usingsaid coefficients from said coefficient generating means, to obtaincolor-converted image information.

It may be so arranged that

said multiplying means performs, by setting said calculationcoefficients aq1 to aq6 and ap1 to ap6 to a value given by 2^(n), with nbeing an integer 0, 1, 2, . . . , calculation on said hue data and saidcalculation coefficients, by means of bit shifting.

According to a second aspect of the invention, there is provided a colorconversion method for obtaining color-converted image information,comprising the steps of:

calculating maximum and minimum values β and α of image information foreach pixel;

calculating hue data r, g, b, y, m and c based on said image informationand said calculated maximum and minimum values β and α;

generating comparison-result data using said calculated hue data;

performing calculation on said comparison-result data and saidcalculated hue data;

performing calculation between said respective hue data; and

performing matrix calculation using said comparison-result data, outputsof said calculation, said calculated hue data, said minimum value α, andbased on predetermined matrix coefficients.

The method may further comprise the steps of:

calculating the maximum and minimum values β and α of image data R, Gand B which is image information for each pixel;

calculating hue data r, g, b, y, m and c by performing subtractionr=R−α,g=G−α,b=B−α,y=β−B,m=β−G, andc=β−R,on said inputted image data R, G and B and said maximum and minimumvalues β and α;

multiplying said hue data by predetermined calculation coefficients aq1to aq6 and ap1 to ap6;

obtaining comparison-result data between respective outputs of saidmultiplication, said comparison-result data beinghry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),with min(A, B) representing the minimum value of A and B;

obtaining comparison-result data between said comparison-result data andsaid hue data;

obtaining product terms based on said comparison-result data hry, hrm,hgy, hgc, hbm and hbc, and said hue data;

obtaining product terms, and fraction terms based on said hue data; and

performing matrix calculation using said comparison-result data, theresults of said calculation, said hue data, and said minimum value α, tothereby obtain color-converted image data.

The method may further comprise the steps of:

calculating the maximum and minimum values β and α of complementarycolor data C, M and Y of cyan, magenta and yellow which is imageinformation for each pixel;

calculating hue data r, g, b, y, m and c by performing subtractionr=β−C,g=β−M,b=β−Y,y=Y−α,m=M−α, andc=C−α,on said complementary color data C, M and Y and said maximum and minimumvalues β and α;

multiplying said hue data by predetermined calculation coefficients aq1to aq6 and ap1 to ap6;

obtaining comparison-result data between respective outputs of saidmultiplication, said comparison-result data beinghry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),with min(A, B) representing the minimum value of A and B;

obtaining comparison-result data between said comparison-result data andsaid hue data;

obtaining product terms based on said comparison-result data hry, hrm,hgy, hgc, hbm and hbc, and said hue data;

obtaining product terms, and fraction terms based on said hue data; and

performing matrix calculation using said comparison-result data, theresults of said calculation, said hue data, and said minimum value α, tothereby obtain color-converted image data.

The method may further comprise the steps of:

calculating the maximum and minimum values β and α of image data R, Gand B which is image information for each pixel;

calculating hue data r, g, b, y, m and c by performing subtractionr=R−α,g=G−α,b=B−α,y=β−B,m=β−G, andc=β−R,on said image data R, G and B and said maximum and minimum values β andα;

multiplying said hue data by predetermined calculation coefficients aq1to aq6 and ap1 to ap6;

obtaining comparison-result data between respective outputs of saidmultiplication, said comparison-result data beinghry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),with min(A, B) representing the minimum values of A and B;

obtaining comparison-result data between said comparison-result data andsaid hue data;

obtaining comparison-result data between said hue data r, g, and b, andbetween said hue data y, m and c;

obtaining product terms based on said comparison-result data hry, hrm,hgy, hgc, hbm and hbc, and said hue data;

obtaining product terms based on said hue data; and

performing matrix calculation using said comparison-result data, theresults of said calculation, said hue data, and said minimum value α, tothereby obtain color-converted image data.

The method may further comprise the steps of:

calculating the maximum and minimum values β and α of complementarycolor data C, M and Y which is image information for each pixel;

calculating hue data r, g, b, y, m and c by performing subtractionr=β−C,g=β−M,b=β−Y,y=Y−α,m=M−α, andc=C−α,on said complementary color data C, M and Y and said maximum and minimumvalues β and α;

multiplying said hue data by predetermined calculation coefficients aq1to aq6 and ap1 to ap6;

obtaining comparison-result data between respective outputs of saidmultiplication, said comparison-result data beinghry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),with min(A, B) representing the minimum value of A and B;

obtaining comparison-result data between said comparison-result data andsaid hue data;

obtaining comparison-result data between said hue data r, g and b, andbetween said hue data y, m and c,

obtaining product terms based on said comparison-result data hry, hrm,hgy, hgc, hbm and hbc, and said hue data;

obtaining product terms based on said hue data; and

performing matrix calculation using said comparison-result data, theresults of said calculation, said hue data, and said minimum value α, tothereby obtain color-converted image data.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings:

FIG. 1 is a block diagram showing an example of configuration of a colorconversion device of Embodiment 1;

FIG. 2 is a block diagram showing an example of configuration of apolynomial calculator in the color conversion device of Embodiment 1;

FIG. 3 is a table showing an example of the relation between the valueof the identification code and the maximum and minimum values β and α,and zero hue data in the color conversion device of Embodiment 1;

FIG. 4 is a table showing the operation of a zero remover of thepolynomial calculator in the color conversion device of Embodiment 1;

FIG. 5 is a block diagram showing a part of an example of configurationof a matrix calculator in the color conversion device of Embodiment 1;

FIGS. 6A to 6F are schematic diagram showing the relations between thesix hues and hue data;

FIGS. 7A to 7F are schematic diagram showing the relations between thehues and the product terms in the color conversion device of Embodiment1;

FIGS. 8A to 8F are schematic diagrams showing the relations between thehues and the first order terms using comparison-result data in the colorconversion device of Embodiment 1;

FIGS. 9A to 9F are schematic diagrams showing the relations between thehues and the first order terms using comparison-result data whencalculation coefficients are changed in a calculation coefficientgenerator of the polynomial calculator in the color conversion device ofEmbodiment 1;

FIGS. 10A to 10F are schematic diagrams showing the relations betweenthe hues and the second-order terms using comparison-result data in thecolor conversion device of Embodiment 1;

FIGS. 11A and 11B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 1;

FIG. 12 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 2;

FIG. 13 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 3;

FIG. 14 is a block diagram showing a part of a configuration of a matrixcalculator 4b in the color conversion device of Embodiment 3;

FIG. 15 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 4;

FIG. 16 is a block diagram showing another example of configuration of apolynomial calculator in a color conversion device of Embodiment 5;

FIGS. 17A to 17F are schematic diagrams showing the relations betweenthe hues and the second-order terms using comparison-result data in thecolor conversion device of Embodiment 5;

FIGS. 18A and 18B are tables showing the relations between the hues andinter-hue areas and the effective calculation terms in the colorconversion device of Embodiment 5;

FIG. 19 is a block diagram showing another example of configuration of apolynomial calculator in a color conversion device of Embodiment 9;

FIGS. 20A to 20F are schematic diagrams showing the relations betweenthe hues and the first-order terms using comparison-result data in thecolor conversion device of Embodiment 9;

FIGS. 21A and 21B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 9;

FIG. 22 is a block diagram showing another example of configuration apolynomial calculator in a color conversion device of Embodiment 13;

FIGS. 23A and 23B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 13;

FIG. 24 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 17;

FIG. 25 is a block diagram showing an example of configuration of apolynomial calculator in the color conversion device of Embodiment 17;

FIG. 26 is a block diagram showing a part of an example of configurationof a matrix calculator in the color conversion device of Embodiment 17;

FIGS. 27A to 27F are schematic diagrams showing the relations betweenthe hues and the first-order terms in the color conversion device ofEmbodiment 17;

FIGS. 28A and 28B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 17;

FIG. 29 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 18;

FIG. 30 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 19;

FIG. 31 is a view showing a part of an example of configuration of amatrix calculator 4d in the color conversion device of Embodiment 19;

FIG. 32 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 20;

FIG. 33 is a block diagram showing another example of configuration of apolynomial calculator in a color conversion device of Embodiment 21;

FIGS. 34A and 34B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 21;

FIG. 35 is a block diagram showing another example of configuration of apolynomial calculator in a color conversion device of Embodiment 25;

FIGS. 36A and 36B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 25;

FIG. 37 is a block diagram showing another example of configuration apolynomial calculator in the color conversion device of Embodiment 29;

FIGS. 38A and 38B are tables showing the relations between the hues andinter-hue areas, and the effective calculation terms in the colorconversion device of Embodiment 29;

FIG. 39 is a block diagram showing an example of configuration of aconventional color conversion device;

FIGS. 40A to 40F are schematic diagrams showing the relations betweensix hues and hue data in the conventional color conversion device; and

FIGS. 41A to 41F are schematic diagrams showing the relations betweenthe hues and the product terms in a matrix calculator in theconventional color conversion device.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Next, the preferred embodiments of the present invention will bedescribed in detail with reference to the accompanying drawings.

Embodiment 1

FIG. 1 is a block diagram showing an example of configuration of a colorconversion device of Embodiment 1 of the present invention. In thedrawing, reference marks R, G and B denote image data which are imageinformation for respective pixels. Reference numeral 1 denotes a minimumand maximum calculator for calculating a maximum value β and a minimumvalue α of the inputted image data R, G and B, and generating andoutputting an identification code S1 for indicating, among the six huedata, data which are zero, as will be better understood from thefollowing description; 2, a hue data calculator for calculating hue datar, g, b, y, m and c from the image data R, G and B and the outputs fromthe minimum and maximum calculator; 3, a polynomial calculator; 4, amatrix calculator; 5, a coefficient generator; and 6, a synthesizer.

FIG. 2 is a block diagram showing an example of configuration of thepolynomial calculator 3. In the drawing, a reference numeral 11 denotesa zero remover for removing, from the inputted hue data, data which isof a value zero; 12a and 12b, multipliers; 13a and 13b, adders; 14a and14b, dividers; and 15, a calculation coefficient generator forgenerating and outputting calculation coefficients based on theidentification code from the minimum and maximum calculator 1. Referencenumerals 16a and 16b denote arithmetic units for performingmultiplication between the calculation coefficients outputted from thecalculation coefficient generator 15 and the inputted data; and 17 and18, minimum selectors for selecting and outputting the minimum value ofthe inputted data. Reference numeral 19 denote a multiplier.

Next, the operation will be described. The inputted image data R, G andB (Ri, Gi and Bi) are sent to the minimum and maximum calculator 1 andthe hue data calculator 2. The minimum and maximum calculator 1calculates and output a maximum value β and a minimum value α of theinputted image data Ri, Gi and Bi, and also generates and outputs anidentification code S1 for indicating, among the six hue data, datawhich are zero. The hue data calculator 2 receives the image data Ri, Giand Bi and the maximum and minimum values β and α from the minimum andmaximum calculator 1, performs subtraction of r=Ri−α, g=Gi−α, b=Bi−α,y=β−Bi, m=β−Gi and c=β−Ri, and outputs six hue data r, g, b, y, m and c.

The maximum and minimum values β and α calculated by the minimum andmaximum calculator 1 are respectively represented as follows: β=MAX (Ri,Gi, Bi), and α=MIN (Ri, Gi, Bi). Since the six hue data r, g, b, y, mand c calculated by the hue data calculator 2 are obtained by thesubtraction of r=Ri−α, g=Gi−α, b=Bi−α, y=β−Bi, m=β−Gi and c=β−Ri, thereis a characteristic that at least two among these six hue data are of avalue zero. For example, if a maximum value β is Ri and a minimum valueα is Gi (β=Ri, and α=Gi), g=0 and c=0. If a maximum value β is Ri and aminimum value α is Bi (β=Ri, and α=Bi), b=0 and c=0. In other words, inaccordance with a combination of Ri, Gi and Bi which are the largest andthe smallest, respectively, one of r, g and b, and one of y, m and c, i.e., in total two of them have a value zero.

Thus, the minimum and maximum calculator 1 generate and outputs theidentification code S1 for indicating, among the six hue data, datawhich are zero. The identification code S1 can assume one of the sixvalues, depending on which of Ri, Gi and Bi are of the maximum andminimum values β and α. FIG. 3 shows a relationship between the valuesof the identification code S1 and the maximum and minimum values β and αof Ri, Gi and Bi and hue data which has a value zero. In the drawing,the values of the identification code S1 represent just an example, andthe values may be other than those shown.

Then, the six hue data r, g, b, y, m and c outputted from the hue datacalculator 2 are sent to the polynomial calculator 3, and the hue datar, g and b are also sent to the matrix calculator 4. The polynomialcalculator 3 also receives the identification code S1 outputted from theminimum and maximum calculator 1, and performs calculation by selecting,from the hue data, two data Q1 and Q2 which are not zero, and from thehue data y, m and c, two data P1 and P2 which are not of a value zero.Next, this operation will be described by referring to FIG. 2.

The hue data from the hue data calculator 2 and the identification codeS1 from the minimum and maximum calculator 1 are inputted to the zeroremover 11 in the polynomial calculator 3. The zero remover 11 outputs,based on the identification code S1, the two data Q1 and Q2 which arenot of a value zero, among the hue data r, g and b and the two data P1and P2 which are not of a value zero, among the hue data y, m and c.Here, the data Q1, Q2, P1 and P2 outputted from the zero remover 11 arethe hue data excluding data which are of a value zero, and satisfy therelationships Q1≧Q2 and P1≧P2. In other words, Q1, Q2, P1 and P2 aredetermined as shown in FIG. 4, and then outputted. For example, In FIGS.3 and 4, if an identification code S1 is of a value zero, Q1 and Q2 areobtained from the hue data r and b, and P1 and P2 are obtained from thehue data y and m, and since the maximum value β is Ri and the minimumvalue α is Gi, r (=β−α)≧b (=Bi−α) and m (−β−α)≧y (β−Bi), so the outputsare given by Q1=r, Q2=b, P1=m and P2=y. As in the case of FIG. 3, thevalues of identification code S1 in FIG. 4 represent just an example,and may be other than those shown in FIG. 4.

The data Q1 and Q2 outputted from the zero remover 11 are inputted tothe multiplier 12a, which calculates and outputs the product T3=Q1*Q2.The data P1 and P2 outputted from the zero remover 11 are inputted tothe multiplier 12b, which calculates and outputs the product T1=P1*P2.The adders 13a and 13b respectively output the sums Q1+Q2 and P1+P2. Thedivider 14a receives T3 from the multiplier 12a and Q1+Q2 from the adder13a, and outputs a quotient T4=T3/(Q1+Q2). The divider 14b receives T1from the multiplier 12b and P1+P2 from the adder 13b, and outputs aquotient T2=T1/(P1+P2).

The identification code S1 is inputted from the minimum and maximumcalculator 1 to the calculation coefficient generator 15, whichgenerates signals indicating calculation coefficients aq and ap, usedfor multiplication on the data Q2 and P2, based on the identificationcode S1, and the calculation coefficients aq are supplied to thearithmetic unit 16a, and the coefficients ap are outputted to thearithmetic unit 16b. These calculation coefficients aq and apcorresponding to the respective hue data Q2 and P2 are generated basedon the identification code S1, and each of the calculation coefficientsaq and ap can assume one of the six values, corresponding to the valueof the identification code S1, as shown in FIG. 4. The arithmetic unit16a receives the data Q2 from the zero remover 11, performsmultiplication of aq*Q2, with aq being the calculation coefficient fromthe calculation coefficient generator 15, and sends the result to theminimum selector 17. The arithmetic unit 16b receives the data P2 fromthe zero remover 11, performs multiplication of ap*P2, with ap being thecalculation coefficient from the calculation coefficient generator 15,and sends the result to the minimum selector 17.

The minimum selector 17 selects the minimum value t6=min (aq*Q2, ap*P2)of the outputs from the arithmetic units 16a and 16b, and outputs theminimum value to the minimum selector 18, and the multiplier 19. Thedata Q1 outputted from the zero remover 11 is also inputted to theminimum selector 18. The minimum selector 18 thus outputs the minimumvalue T5=min(Q1, min(aq*Q2, ap*P2) of Q1 and t6=min(aq*Q2, ap*P2). Themultiplier 19 also receives the data Q1 outputted from the zero remover11, and performs multiplication Q1 and t6=min(aq*Q2, ap*P2) and outputsthe product T6=Q1*min(aq*Q2, ap*P2). The foregoing polynomial data T1,T2, T3, T4, T5, and T6 are outputted from the polynomial calculators 3.The outputs of this polynomial calculator 3 are sent to the matrixcalculator 4.

The coefficient generator 5 shown in FIG. 1 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the same to thematrix calculator 4. The matrix calculator 4 receives the hue data r, gand b from the hue data calculator 2, the polynomial data T1 to T6 fromthe polynomial calculator 3 and the coefficients U from the coefficientgenerator 5, and outputs the results of calculation according to thefollowing formula (34) as image data R1, G1 and B1. $\begin{matrix}{\begin{bmatrix}{R1} \\{G1} \\{B1}\end{bmatrix} = {{({Eij})\begin{bmatrix}r \\g \\b\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T2} \\{T3} \\{T4} \\{T5} \\{T6}\end{bmatrix}}}} & (34)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 6.

FIG. 5 is a block diagram showing an example of configuration of part ofthe matrix calculator 4. Specifically, it shows how Ri is calculated andoutputted. In the drawing, reference numerals 20a to 29g denotemultipliers; 21a to 21f, adders.

Next, the operation of the matrix calculator 4 of FIG. 5 will bedescribed. The multipliers 20a to 20g receive the hue data r, thepolynomial data Ti to T6 from the polynomial calculator 3 and thecoefficients U (Eij) and U (Fij) from the coefficient generator 5, andoutput the products thereof. The adders 21a and 21b receive the productsoutputted from the multipliers 20b to 20e, add the inputted data andoutputs the sums thereof. The adder 21c receives the products outputtedfrom the multipliers 20f and 20g, and outputs the sum thereof. The adder21d adds the data from the adders 21a and 21b, and the adder 21e addsthe outputs from the adders 21d and 21c. The adder 21f adds the outputfrom the adder 21e and the output from the multiplier 20a, and outputsthe sum total thereof as image data R1. In the example of configurationshown in FIG. 5, if the hue data r is replaced by the hue data g or b,image data G1 or Bi can be calculated.

The part of the coefficients (Eij) and (Fij) corresponding to the huedata r, g and b are used. In other words, if three configuration, eachsimilar to that of FIG. 5, are used in parallel for the hue data r, gand b, matrix calculation can be performed at a higher speed.

The synthesizer 6 receives the image data R1, G1 and B1 from the matrixcalculator 4 and the minimum value α outputted from the minimum andmaximum calculator 1 representing the achromatic data, performsaddition, and outputs image data R, G and B. The formula used forobtaining the image data obtained by color conversion by the method ofFIG. 1 is therefore as follows:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j≦1to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),and aq1 to aq6 and ap1 to ap6 indicate calculation coefficientsgenerated by the calculation coefficient generator 15 of FIG. 2.

The difference between the number of calculation terms in the formula(1) and the number of calculation terms in FIG. 1 is that FIG. 1 shows amethod of calculation for each pixel excluding data resulting in thecalculation terms which are of a value zero, while the formula (1)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as described above with reference to FIG. 3. For example, in thecase where the value of the identification code S1 is 0, with themaximum and minimum values β and α shown in FIG. 3 being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fourcalculation terms in the formula (1) except the six calculation terms ofm*y, b*r, b*r/(b+r), m*y/(m+y), min (r, hrm) and r*hrm, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fourcalculation terms minus the six calculation terms) are of a value zero.Accordingly, twenty-four polynomial data for one pixel of the formula(1) can be reduced to six effective data, and this reduction is achievedby exploiting a characteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

FIGS. 6A to 6F schematically show relations between the six hues and thehue data y, m, c, r, g and b. Each hue data relates to three hues.

FIGS. 7A to 7F schematically show relations between the six hues and theproduct terms m*y, r*g, y*c, g*b, c*m and b*r, and it can be understoodthat each product term is a second-order term for a specified hue. Forexample, if W is a constant, since r=W and g=b=0 hold for red, y=m=W andc=0 are obtained. Accordingly, y*m=W*W is realized, and the other fiveterms are all zero. In other words, only m*y is an effectivesecond-order term for red. Similarly, y*c is the only effective term forgreen; c*m for blue, g*b for cyan; b*r for magenta; and r*g for yellow.

Each of the foregoing formulae (1) and (34) includes a first-orderfraction term effective only for one hue. Those fraction terms are:r*g/(r+g), g*b/(g+b), b*r/(b+r), m*y/(m+y), c*m/(c+m), and y*c/(y+c),and there are thus six such fraction terms. These have first-order termcharacteristics. For example, if W is a constant, since r=W and g=b=0hold for red, y=m=W and c=0 are obtained. Then, m*y/(m+y)=W/2, and theother five terms are all zero. Accordingly, only m*y/(m+y) is aneffective first-order term for red. Similarly, y*c/(y+c) is an onlyeffective first-order term for green; c*m/(c+c) for blue; g*b(g+b) forcyan; b*r/(b+r) for magenta; and r*g/(r+g) for yellow. Here, if anumerator and a denominator are both zero, then a first-order termshould be set to zero.

Next, a difference between the first-order and second-order terms willbe described. As described above, for red, if W is a constant, m*y=W*Wis realized, and the other product terms are all zero. Here, since theconstant W indicates the magnitudes of the hue signals y and m, themagnitude of the constant W depends on the color brightness or chroma.With m*y=W*W, the product term m*y is a second-order function forchroma. The other product terms are also second-order functions forchroma regarding the hues to which these terms are effective.Accordingly, influence given by each product term to color reproductionis increased in a second-order manner as chroma is increased. In otherwords, the product term is a second-order term which serves as asecond-order correction term for chroma in color reproduction.

On the other hand, for red, if W is a constant, m*y/(m+y)=W/2 isrealized, and the other fraction terms are all zero. Here, the magnitudeof the constant W depends of color brightness or chroma. Withm*y/(m+y)=W/2, the fraction term m*y/(m+y) is a first-order function forchroma. The other fraction terms are also first-order functions forchroma regarding the hues to which these terms are effective.Accordingly, the influence given by each fraction term to colorreproduction is a first-order function for chroma. In other words, thefraction term is a first-order term which serves as a first-ordercorrection term for chroma in color reproduction.

FIGS. 8A to 8F schematically show relations between the six hues andfirst-order calculation terms using comparison-result data, min(r, hry,min(g, hgy), min(g, hgc), min (b, hbc), min(b, hbm) and min(r, hrm). Itis assumed that the values of calculation coefficients aq1 to aq6 andap1 to ap6, inhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m),in the foregoing formula (1) and (34) are set to “1”. It can beunderstood from FIGS. 8A to 8F, that the first-order calculation termsusing the comparison-result data relate to changes in the six inter-hueareas of red-green, yellow-green, green-cyan, cyan-blue, blue-magenta,and magenta-red. In other words, for a red-yellow inter-hue area, r=W,g=W/2, b=0. W being a constant, so that y=W, m=W/2, c=0, so that min(r,hry)=min(r, min(g, m))=W/2, and the five other terms are all zero.Accordingly, only min(r, hry)=min(r, min(g, m)) is an effectivefirst-order calculation term for red-yellow. Similarly, only min(g, hgy)is an effective first-order calculation term for yellow-green; min(g,hgc) for green-cyan; min(b, hbc) for cyan-blue; min(b, hbm) forblue-magenta; and min(r, hrm) for magenta-red.

FIGS. 9A to 9F schematically show relations between the six hues and thefirst-order calculation terms using comparison-result data when thecalculation coefficients aq1 to aq6 and ap1 to ap6 are changed in hry,hrm, hgy, hgc, hbm and hbc in the foregoing formulae (1) and (34). Thebroken lines a1 to a6 shows the characteristics when, for example, aq1to aq6 assume values larger than ap1 to ap6. The broken lines b1 to b6shows the characteristics when, for example, ap1 to ap6 assume valueslarger than aq1 to aq6.

Specifically, for red to yellow, only min(r, hry)=min (r, min(aq1*g,ap1*m)) is an effective first-order calculation term. If, for example,the ratio between aq1 and ap1 is 2:1, the peak value of the calculationterm is shifted toward red, as indicated by the broken line a1 in FIG.9A, and thus it can be made an effective calculation term for an areacloser to red in the inter-hue area of red-yellow. On the other hand,for example if the ratio between aq1 and ap1 is 1:2, the relationship isas indicated by the broken line b1 in FIG. 9A, the peak value of thecalculation term is shifted toward yellow, and thus it can be made aneffective calculation term for an area closer to yellow in the interline area of red to yellow. Similarly, by respectively changing:

-   aq3 and ap3 in min(g, hgy) for yellow to green,-   aq4 and ap4 in min(g, hgc) for green to cyan,-   aq6 and ap6 in min(b, hbc) for cyan to blue,-   aq5 and ap5 in min(b, hbm) for blue to magenta and-   aq2 and ap2 in min(r, hrm) for magenta to red,    in the inter-hue areas between adjacent ones of these hues,    effective areas can be changed.

FIGS. 10A to 10F schematically show relations between the six hues andsecond-order terms of r*hry, g*hgy, g*hgc, b*hbc, b*hbm and r*hrm, whichare product terms based on the comparison-result data and the hue data.In the drawings, broken lines c1 to c6 and d1 to d6 representcharacteristics obtained when the calculation coefficients aq1 to aq6and ap1 to ap6 in hry, hrm, hgy, hgc,-hbm and hbc are changed. Solidlines represent characteristics obtained when the values of thecalculation coefficients aq1 to aq6 and ap1 to ap6 are 1. From FIGS. 10Ato 10F, it can be understood that the second-order terms usingcomparison-result data contribute to changes in the inter-hue areas ofred to yellow, yellow to green, green to cyan, cyan to blue, blue tomagenta, and magenta to red. In other words, for example, for theinter-hue area of red to yellow, since r=W, g=W/2 and b=0, with W beinga constant, y=W, m=W/2, c=0, and r*hry=r*min(g, m)=W*W/2, and the otherfive terms are all zero. Accordingly, only r*hry is an effectivesecond-order term for red-yellow. Similarly, only g*hgy is an effectiveterm for yellow-green; g*hgc for green-cyan; b*hbc for cyan-blue; b*hbmfor blue-magenta; and r*hrm for magenta-red.

Next, differences between the first-order terms and the second-orderterms among the calculation terms using comparison-result data will bedescribed. As described above, for the inter-hue area of red-yellow, forexample, r*hry=W*W/2, with W being a constant, and the other productterms are all zero. Then, min(r, hry)=W/2, and the other terms are allzero. Here, since the constant W represents a magnitude of a hue signal,a size of the constant W depends on color brightness or chroma of apixel, and the product term r*hry is a second-order function of thechroma. The other product terms are also second-order functions of thechroma in the inter-hue areas where the terms are effective.Accordingly, an effect of each product term on color reproduction isincreased as in a second-order fashion with the increase of the chroma.In other words, the product term is a second-order term which serves asa second-order compensation term for the chroma in the colorreproduction.

On the other hand, with regard to the first-order term min(r, hry), thefirst-order term min(r, hry)=W/2, and is a first-order function of thechroma. The other terms are also first-order functions of the chroma inthe inter-hue areas where the terms are effective. Accordingly, aneffect of the first-order term based on each comparison-result data is afirst-order function of the chroma. In other words, the first-order termbased on each comparison-result data is a first-order term which servesas a first-order compensation term for the chroma in the colorreproduction.

FIGS. 11A to 11B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator 5 changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3 are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

Next, an example of coefficients generated by the coefficient generator5 of Embodiment 1 described above with reference to FIG. 1 will bedescribed. The following formula (33) shows an example of coefficients U(Eij) generated by the coefficient generator 5. $\begin{matrix}{({Eij}) = \begin{bmatrix}1 & 0 & 0 \\0 & 1 & 0 \\0 & 0 & 1\end{bmatrix}} & (33)\end{matrix}$

If the coefficients U (Eij) in the foregoing formula are all zero thisrepresents the case where no color conversion is executed. Among thecoefficients U (Fij) for the product terms, the fraction terms, and thefirst-order and second-order terms using comparison-result data,coefficients relating to the calculation terms for the hues or theinter-hue areas to be changed are determined, and the other coefficientsare set to be zero. In this way, adjustment of only the target hues orinter-hue areas can be made. For example, by setting the coefficientsfor the first-order calculation term m*y/(m+y) for red, the hue red ischanged, and by changing the inter-hue area red-yellow, the coefficientsof the first-order term min(r, hry) and the coefficients of thesecond-order term r*hry are used.

Furthermore, if, in the polynomial calculator 3, the values ofcalculation coefficients aq1 to aq6 and ap1 to ap6 inhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m)are changed so as to assume integral values of 1, 2, 4, 8, . . . , i.e.,2^(n) (where n is an integer), multiplication can be achieved in thearithmetic units 16a and 16b by bit shifting.

As apparent from the foregoing, by changing the coefficients of thecalculation terms relating to specific hues or inter-hue areas, it ispossible to adjust only the target hue among the six hues of red, blue,green, yellow, cyan and magenta, without affecting other hues, and it ispossible to correct the six inter-hue areas of red-yellow, yellow-green,green-cyan, cyan-blue, blue-magenta, and magenta-red independently.

Moreover, the product terms and the second-order terms usingcomparison-result data represent second-order calculations with respectto the chroma, and the fraction terms and the first-order terms usingcomparison-result data represent first-order calculations with respectto the chroma, and by using both the first-order terms and thesecond-order terms, it is possible to correct the non-linearity of thechroma in image printing or the like. Accordingly, it is possible toobtain a color conversion device or color conversion method with whichthe conversion characteristics can be flexibly varied, and which doesnot require a large capacity memory. In addition, in the Embodiment 1,the color conversion is performed on the input image data R, G, and B,so that it is possible to perform good color reproduction in a displaydevice such as a monitor, or an image processing device using image datarepresented by R, G and B, and greater advantages can be obtained.

In Embodiment 1 described above, the hue data r, g and b, y, m and c,and the maximum and minimum values β and α were calculated based on theinputted image data R, G and B so as to obtain the calculation terms forthe respective hues, and after the matrix calculation, the image data R,G and B were obtained. However, after the outputted image data areobtained, the data R, G and B may be converted into complementary colordata C, M and Y. In this case, the same effects will be realized.

Furthermore, in Embodiment 1 described above, the processing wasperformed by the hardware configuration of FIG. 1. Needless to say, thesame processing can be performed by software in the color conversiondevice, and in this case, the same effects as those of Embodiment 1 willbe provided.

Embodiment 2

In Embodiment 1, the hue data r, g and b, y, m and c, and the maximumand minimum values β and α were calculated based on the inputted imagedata R, G and B so as to obtain the calculation terms for the respectivehues, and after the matrix calculation, the image data R, G and B wereobtained. But the image data, R, G and B may first be converted intocomplementary color data C, M and Y, which are an example of imageinformation, and then color conversion may be executed by inputting thecomplementary color data C, M and Y.

FIG. 12 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 2 of the present invention. In thedrawing, the complementary color data Ci, Mi, and Yi are an example ofimage information, reference numerals 3 to 6 denote the same members asthose described with reference to FIG. 1 in connection withEmbodiment 1. Reference numeral 10 denotes a complement calculator; 1b,a minimum and maximum calculator for generating maximum and minimumvalues β and α of complementary color data and an identification codefor indicating, among the six hue data, data which are zero; and 2b, ahue data calculator for calculating hue data r, g, b, y, m and c basedon complementary color data C, M and Y from the complement calculator 10and outputs from the minimum and maximum calculator 1b.

Next, the operation will be described. The complement calculator 10receives the image data R, G and B, and outputs complementary color dataCi, Mi and Yi obtained by determining 1's complements. The minimum andmaximum calculator 1b outputs the maximum and minimum values β and α ofthese complementary color data and an identification code S1 forindicating, among the six hue data, data which are zero.

Then, the hue data calculator 2b receives the complementary color dataCi, Mi and Yi and the maximum and minimum values β and α from theminimum and maximum calculator 1b, performs subtraction of r=β−Ci,g=β−Mi, b=β−Yi, y=Yi−α, m=Mi−α, and c=Ci−α, and outputs six hue data r,g, b, y, m and c. Here, at least two among these six hue data are zero.The identification code S1 outputted from the minimum and maximumcalculator 1b is used for specifying, among the six hue data, data whichis zero. The value of the identification code depends on which of Ci, Miand Yi the maximum and minimum values β and α are. Relations between thedata among the six hue data which are zero, and the values of theidentification code are the same as those in Embodiment 1, and thusfurther explanation will be omitted.

Then, the six hue data r, g, b, y, m and c outputted from the hue datacalculator 2 are sent to the polynomial calculator 3, and the hue datac, m and y are also sent to the matrix calculator 4. The polynomialcalculator 3 also receives the identification code S1 outputted from theminimum and maximum calculator 1, and performs calculation by selecting,from the hue data, two data Q1 and Q2 which are not zero, and from thehue data y, m and c, two data P1 and P2 which are not of a value zero.The operations are similar to those described in connection withEmbodiment 1 with reference to FIG. 2, and their details are omitted.

The outputs from the polynomial calculator 3 are sent to the matrixcalculator 4. The coefficient generator 5 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generalcoefficients to the matrix calculator 4. Based on the hue data c, m andy from the hue data calculator 2b, polynomial data T1 to T6 from thepolynomial calculator 3 and coefficients U from the coefficientgenerator 5, the matrix calculator 4 outputs the results of calculationaccording to the following formula (35), as image data C1, M1 and Y1.$\begin{matrix}{\begin{bmatrix}{C1} \\{M1} \\{Y1}\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T2} \\{T3} \\{T4} \\{T5} \\{T6}\end{bmatrix}}}} & (35)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 6.

The operation at the matrix calculator 4 is similar to that describedwith reference to FIG. 5 in connection with Embodiment 1, but theinputted hue data is c (or m, y) and C1 (or M1, Y1) is calculated andoutputted. The detailed description thereof is therefore omitted.

The synthesizer 6 receives the image data C1, M1 and Y1 from the matrixcalculator 4 and the minimum value α outputted from the minimum andmaximum calculator 1b representing the achromatic data, performsaddition, and outputs image data C, M and Y. The formula used forobtaining the color-converted image data by the color-conversion deviceof FIG. 12 is therefore as follows:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 of FIG. 2.

The difference between the number of calculation terms in the formula(2) and the number of calculation terms in FIG. 12 is that FIG. 12 showsa method of calculation for each pixel excluding data resulting in thecalculation terms which are of a value zero, while the formula (2)represents a general formula for a set of pixels. In other words, as inEmbodiment 1, the six hue data have such a characteristic that at leasttwo of them are zero. For example, in the case where the value of theidentification code S1 is 0, with the maximum and minimum values β and αshown in FIG. 3 being respectively Ri and Gi, equations g=0 and c=0hold. Accordingly, the twenty-four calculation terms in the formula (2)except the six calculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y),min(r, hrm) and r*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (2) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data.

The combination of effective data changes depending on the image data ofthe target pixel (the pixel in question), and all the polynomial dataare effective in all the image data.

The calculation terms of the above formula (2) produced by thepolynomial calculator are identical to those of formula (1) inEmbodiment 1, and the relations between the six hues and inter-hueareas, and the effective calculation terms are identical to those shownin FIGS. 11A and 11B. Accordingly, as in the case of Embodiment 1, bychanging coefficients of the effective calculation terms for hues orinter-hue areas to be adjusted in the coefficient generator 5, it ispossible to adjust only the target hues or inter-hue area.

Further, by changing coefficients generated by the calculationcoefficient generator 15 in the polynomial calculator 3, the calculationterms effective in the areas can be changed without influencing theother hues.

If the coefficients U (Eij) generated by the coefficient generator 5 ofEmbodiment 2 are set as in the formula (33), and the coefficients U(Fij) are all set to zero, no color conversion is performed, as wasdescribed in connection with Embodiment 1. By means of thosecoefficients U (Fij) for the product terms, fraction terms andcalculation terms based on comparison-result data, the hues or inter-hueareas to which the calculation terms relate can be adjusted. By settingthe coefficients for the calculation terms which relate to the hues orinter-hue areas to be changed, and setting the other coefficients tozero, it is possible to adjust only the particular hues or inter-hueareas.

As apparent from the foregoing, by changing the coefficients of theproduct term and fraction terms relating to specific hues, it ispossible to adjust only the target hue among the six hues of red, blue,green, yellow, cyan and magenta, without affecting other hues. Bychanging the coefficients for the first-order terms and second-orderterms derived through comparison of the hue data, it is possible tocorrect the six inter-hue areas of red-yellow, yellow-green, green-cyan,cyan-blue, blue-magenta, and magenta-red independently.

Moreover, the product terms and the second-order terms usingcomparison-result data represent second-order calculations with respectto the chroma, and the fraction terms and the first-order terms usingcomparison-result data represent first-order calculations with respectto the chroma. By using both the first-order terms and the second-orderterms, it is possible to correct the non-linearity of the chroma inimage printing or the like. Accordingly, it is possible to obtain acolor conversion device or color conversion method with which theconversion characteristics can be flexibly varied, and which does notrequire a large-capacity memory. In addition, in the Embodiment 2, theinput image data R, G, and B are converted to complementary color dataC, M, and Y, and the color conversion is performed on the complementarycolor data C, M, and Y, so that it is possible to perform good colorreproduction of print data C, M, and Y in a printing device or the like.

In the above-description of Embodiment 2, hardware is used to performthe processing of the configuration shown in FIG. 12. Identicalprocessing can be performed by software in the color conversion device,and an effect identical to that of Embodiment 2 can be obtained.

Embodiment 3

In Embodiment 1, part of the matrix calculator 4 is assumed to be asshown in the block diagram of FIG. 5, and the hue data and thecalculation terms, and the minimum value α of R, G, B, are addedtogether, as shown in formula (1), to produce the image data R, G, B. Asan alternative, coefficients for the minimum value α which is achromaticdata may be generated in the coefficient generator, as shown in FIG. 13,to adjust the achromatic component.

FIG. 13 is a block diagram showing an example of configuration of thecolor conversion device according to Embodiment 3. In the figure,reference numerals 1 to 3 denote numbers identical to those described inconnection with Embodiment 1 with reference to FIG. 1. Reference numeral4b denotes a matrix calculator, and 5b denotes a coefficient generator.

The operation will next be described. The operations at the minimum andmaximum calculator 1 for determining the maximum value β, the-minimumvalue α, and the identification code S1, based on the input data, at thehue data calculator 2 for determining the six hue data, and at thepolynomial calculator 3 for determining the calculation terms areidentical to those of Embodiment 1, so their details are omitted.

The coefficient generator 5b in FIG. 13 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4b. Based on the hue data r, g,and b from the hue data calculator 2, polynomial data T1 to T6 from thepolynomial calculator 3, the minimum value from the minimum and maximumcalculator 1, and coefficients U from the coefficient generator 5b, thematrix calculator 4b performs calculation in accordance with thefollowing formula (36) to adjust the achromatic component.$\begin{matrix}{\begin{bmatrix}R \\G \\B\end{bmatrix} = {{({Eij})\begin{bmatrix}r \\g \\b\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T2} \\{T3} \\{T4} \\{T5} \\{T6} \\\alpha\end{bmatrix}}}} & (36)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 7.

FIG. 14, which is a block diagram, shows an example of configuration ofpart of the matrix calculator 4b. In FIG. 14, reference numerals 20a to20g, 21a to 21f denote members identical to those in the matrixcalculator 4 of Embodiment 1. Reference numeral 22 denotes a multiplierwhich receives the minimum value α from the minimum and maximumcalculator 1 representing the achromatic component, and the coefficientsU from the coefficient generator 5b, and determines the product thereof.Reference numeral 23 denotes an adder.

Next, the operation of the matrix calculator 4b of FIG. 14 will bedescribed. The multipliers 20a to 20g receive the hue data r, thepolynomial data T1 to T6 from the polynomial calculator 3 and thecoefficients U (Eij) and U (Fij) from the coefficient generator 5, andoutput the products thereof. The adders 21a and 21f add the productsand/or sums. Their operations are identical to those in the matrixcalculator 4 in Embodiment 1. The multiplier 22 receives he minimumvalue α of the R, G, B, from the minimum and maximum calculator 1, whichcorresponds to the achromatic component, and the coefficients U (Fij)from the coefficient generator 5b, and determines the product thereof,which is sent to the adder 23, and added to the output of the adder 21f.The total sum is outputted as output R of the image data R. In theexample of configuration shown in FIG. 14, if the hue data r is replacedby the hue data g or b, image data G or B can be calculated.

The part of the coefficients (Eij) and (Fij) corresponding to the huedata r, g and b are used. In other words, if three configurations, eachsimilar to that of FIG. 14, are used in parallel for the hue data r, gand b, matrix calculation can be performed at a higher speed.

Thus, the matrix calculator 4b performs calculation on the variouscalculation terms and the minimum value α which is the achromatic data,using coefficients, adding the result to the hue data, to produce imagedata R, G and B. The formula used for producing the image data is givenbelow:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 25.

The difference between the number of calculation terms in the formula(3) and the number of calculation terms in FIG. 13 is that FIG. 13 showsa method of calculation for each pixel excluding data resulting in thecalculation terms in the polynomial calculator which are of a valuezero, while the formula (3) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum value β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (3) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(r, hrm), r*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (3) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

If all the coefficients relating to the minimum value α are of a value“1,” the achromatic data is not converted, and will be a value identicalto that of the achromatic data in the input data. If the coefficients inthe matrix calculation are changed, it is possible to select reddishblack, bluish black or the like, so that it is possible to adjust theachromatic component.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 3, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

In Embodiment 3 described above, the hue data r, g and b, y, m and c,and the maximum and minimum values β and α were calculated based on theinputted image data R, G and B so as to obtain the calculation terms forthe respective hues, and after the matrix calculation, the image data R,G and B were obtained. However, after the outputted image data areobtained, the data R, G and B may be converted into complementary colordata C, M and Y. In this case, the same effects will be realized.

In the above-description of Embodiment 3, hardware is used to performthe required processing. Identical processing can be performed bysoftware, as was also stated in connection with Embodiment 1, and aneffect identical to that of Embodiment 3 can be obtained.

Embodiment 4

In Embodiment 2, the configuration is such that the hue data and thecalculation terms, and the minimum value α are added together, as shownin formula (2). As an alternative, coefficients for the minimum value αwhich is achromatic data may be generated in the coefficient generator,as shown in FIG. 15, to adjust the achromatic component.

FIG. 15 is a block diagram showing an example of configuration of thecolor conversion device according to Embodiment 4. In the figure,reference numerals 10, 1b, 2b and 3 denote members identical to those ofEmbodiment 2 shown in FIG. 12, while reference numerals 4b and 5b denotemembers identical to those of Embodiment 3 shown in FIG. 13.

The operation will next be described. The image data R, G and B areinputted to the complement calculator 10, which produces thecomplementary color data Ci, Mi and Yi by determining 1's complements.The minimum and maximum calculator 1b determines the maximum value β,the minimum value α, and the identification code S1, while the hue datacalculator 2b determines the six hue data. The polynomial calculator 3determines the calculation terms. These operations are identical tothose of Embodiment 2 with regard to the complementary color data C, Mand Y, so their details are omitted.

The coefficient generator 5b in FIG. 15 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4b. Based on the hue data c, m,and y from the hue data calculator 2b, polynomial data T1 to T6 from thepolynomial calculator 3, the minimum value from the minimum and maximumcalculator 1b, and coefficients U from the coefficient generator 5b, thematrix calculator 4b performs calculation in accordance with thefollowing formula (37) to adjust the achromatic component.$\begin{matrix}{\begin{bmatrix}C \\M \\Y\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T2} \\{T3} \\{T4} \\{T5} \\{T6} \\\alpha\end{bmatrix}}}} & (37)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 7.

The operation of the matrix calculator 4b is similar to that describedwith reference to FIG. 14 in connection with Embodiment 3, with theinputted hue data c (or m or y) being substituted to determine andoutput C (or M or Y), so that its details description is omitted.

Thus, the matrix calculator 4b performs calculation on the variouscalculation terms and the minimum value α which is the achromatic data,using coefficients, adding the result to the hue data, to produce imagedata C, M, and Y. The formula used for producing the image data is givenbelow:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 25.

The difference between the number of calculation terms in the formula(4) and the number of calculation terms in FIG. 15 is that FIG. 15 showsa method of calculation for each pixel excluding data resulting in thecalculation terms in the polynomial calculator which are of a valuezero, while the formula (4) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (4) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(r, hrm), r*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (4) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

If all the coefficients relating to the minimum value α are of a value“1,” the achromatic data is not converted, and will be a value identicalto that of the achromatic data in the input data. If the coefficients inthe matrix calculation are changed, it is possible to select reddishblack, bluish black or the like, so that it is possible to adjust theachromatic component.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 4, the color conversion is performed on thecomplementary color data C, M, and Y, having been obtained by conversionfrom the input image data R, G, and B, so that it is possible to achievegood color reproduction in color conversion of the printing data C, M,and Y in a printing device or the like, and greater advantages can beobtained.

In the above-description of Embodiment 4, hardware is used to performthe required processing. Identical processing can be performed bysoftware, as was also stated in connection with the above-describedembodiments, and an effect identical to that of Embodiment 4 can beobtained.

Embodiment 5

In Embodiments 1 to 4 described above, an example of the polynomialcalculator 3 shown in FIG. 2 was used, and the polynomial data of theformulas (1) to (4) are calculated and outputted. As an alternative, aconfiguration shown in FIG. 16 may be used to calculate polynomial data.

FIG. 16 is a block diagram showing another example of configuration ofthe polynomial calculator 3. In the drawing, reference numerals 11 to 18denote members identical to those of the polynomial calculator shown inFIG. 2. Reference numeral 19b denotes a multiplier.

Next, the operation of the polynomial calculator 3 shown in FIG. 16 willbe described. The operation of the zero remover 11, and the operationfor outputting T3=Q1*Q2, T4=T3/(Q1+Q2), T1=P1*P2 and T2=T1/(P1+P2) bythe multipliers 12a and 12b, the adders 13a and 13b and the dividers 14aand 14b and the operation for outputting t6=min (aq*Q2, ap*P2) by thethe calculation coefficient generator 15, the calculators 16a and 16band the minimum value selector 17, and the operation for outputting theminimum values T5=min(Q1, min(aq*Q2, ap*P2)) between Q1 and t6 by theminimum value selector 18 are identical to those of the embodimentdescribed above with reference to FIG. 2. Thus, detailed explanationthereof will be omitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 isalso supplied to the multiplier 19b, which also receives the data P1from the zero remover 11, and performs multiplication P1 byt6=min(aq*Q2, ap*P2), and outputs the product T6′=P1*min(aq*Q2, ap*P2).Accordingly, the polynomial data T1, T2, T3, T4, T5 and T6′ areoutputted from the polynomial calculator shown in FIG. 16, and theseoutputs of the polynomial calculator are sent to the matrix calculator 4or 4b.

Thus, according to the polynomial calculator 3 described with referenceto FIG. 16, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 1 in connection with Embodiment 1 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator shown in FIG. 16.

The difference between the number of calculation terms in the formula(5) and the number of calculation terms in FIG. 16 is that FIG. 16 showsa method of calculation for each pixel excluding data resulting in thecalculation terms which are of a value zero, while the formula (5)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (5) except the six calculation terms of m*y, b*r,b*r/(b+r), m*y/(m+y), min(r, hrm), and m*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at least two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel of the formula (5) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data. The combination ofeffective data is changed according to image data of the target pixel.For all image data, all the polynomial data can be effective.

FIGS. 17A to 17F schematically show relations between the six hues andsecond-order terms of y*hry, y*hgy, c*hgc, c*hbc, m*hbm and m*hrm, whichare product terms based on the comparison-result data and the hue data.In the drawings, broken lines c1 to c6 and d1 to d6 representcharacteristics obtained when the calculation coefficients aq1 to aq6and ap1 to ap6 in hry, hrm, hgy, hgc, hbm and hbc are changed. Solidlines represent characteristics obtained when the values of thecalculation coefficients aq1 to aq6 and ap1 to ap6 are 1. From FIGS. 17Ato 17F, it can be understood that the second-order terms usingcomparison-result data contribute to changes in the inter-hue areas ofred to yellow, yellow to green, green to cyan, cyan to blue, blue tomagenta, and magenta to red.

In other words, for example, for the inter-hue area of red to yellow,since r=W, g=W/2 and b=0, with W being a constant, y=W, m=W/2, c=0, andy*hry=W*W/2, and the other five terms are all zero.

Here, since the constant W represents a magnitude of a hue signal, asize of the constant W depends on color brightness or chroma of a pixel,and the product term r*hry is a second-order function of the chroma. Theother product terms are also second-order functions with respect to thechroma in the inter-hue areas where the terms are effective.Accordingly, an effect of each product term on color reproduction isincreased as in a second-order fashion with the increase of the chroma.In other words, the product term is a second-order term which serves asa second-order compensation term for the chroma in the colorreproduction. Accordingly, only y*hry is an effective second-order termfor red-yellow. Similarly, only y*hgy is an effective term foryellow-green; c*hgc for green-cyan; c*hbc for cyan-blue; m*hbm forblue-magenta; and m*hrm for magenta-red.

FIGS. 18A and 18B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3 are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order calculation terms using comparison-result data based on thehue data, it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 5, the color conversion is performed onthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 5, hardware is used to performthe processing of the configuration of FIG. 16. Identical processing canbe performed by software, and an effect identical to that of Embodiment5 can be obtained.

Embodiment 6

According to the polynomial calculator 3 described with reference toFIG. 16 in connection with Embodiment 5, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 12 inconnection with Embodiment 2 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 16.

The difference between the number of calculation terms in the formula(6) and the number of calculation terms in FIG. 16 is that FIG. 16 showsa method of calculation for each pixel excluding data resulting in thecalculation terms which are of a value zero, while the formula (6)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (6) except the six calculation terms of m*y, b*r,b*r/(b+r), m*y/(m+y), min(r, hrm), and m*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at least two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel of the formula (6) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data. The combination ofeffective data is changed according to image data of the target pixel.For all image data, all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (6) are identical to those of the formula (5) in Embodiment 5,and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 18A and18B. Accordingly, as in Embodiment 5, if the coefficient generatorchanges coefficients for a calculation term effective for a hue or aninter-hue area to be adjusted, only the target hue can be adjusted, andthe inter-hue areas can also be corrected. Further, if coefficientsgenerated by the calculation coefficient generator 15 in the polynomialcalculator 3 are changed, part of the inter-hue area where a calculationterm in the inter-hue area is effective can be changed without givingany influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order calculation terms using comparison-result data based on thehue data, it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 6, the color conversion is performed onthe complementary color data obtained by conversion from the input imagedata R, G, and B, so that it is possible to achieve good colorreproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 7

According to the polynomial calculator 3 described with reference toFIG. 16 in connection with Embodiment 5, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 13 in connection withEmbodiment 3 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(7) and the number of calculation terms in the polynomial calculator inFIG. 16 is that FIG. 16 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (7) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (7) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(r, hrm), m*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (7) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 7, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 8

According to the polynomial calculator 3 described with reference toFIG. 16 in connection with Embodiment 5, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 15 inconnection with Embodiment 4 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(8) and the number of calculation terms in the polynomial calculator inFIG. 16 is that FIG. 16 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (8) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g≦0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (8) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(r, hrm), m*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (8) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 8, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 9

As another example, the polynomial calculator 3 may be formed as shownin FIG. 19, to calculate the polynomial data.

FIG. 19 is a block diagram showing another example of configuration ofthe polynomial calculator 3. In the drawing, reference numerals 11 to 17denote members identical to those of the polynomial calculator shown inFIG. 2. Reference numeral 19b denotes a member identical to those inFIG. 16. Reference numeral 18b denotes a minimum value selector forselecting and outputting the minimum value of the input data.

Next, the operation of the polynomial calculator 3 shown in FIG. 19 willbe described. The operation of the zero remover 11, and the operationfor outputting T3=Q1*Q2, T4=T3/(Q1+Q2), T1=P1*P2 and T2=T1/(P1+P2) bythe multipliers 12a and 12b, the adders 13a and 13b and the dividers 14aand 14b, and the operation for outputting t6=min(aq*Q2, ap*P2) by thethe calculation coefficient generator 15, the calculators 16a and 16band the minimum value selector 17 are identical to those of theembodiment described above with reference to FIG. 2. Thus, detailedexplanation thereof will be omitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 issupplied to the minimum value selector 18b and the multiplier 19b. Theminimum value selector 18b also receives the output data P1 from thezero remover 11, and outputs the minimum value T5′=min(P1, min(aq*Q2,ap*P2) between P1 and t6=min(aq*Q2, ap*P2). The multiplier 19b receivesthe data P1 from the zero remover 11, and the output t6 from the minimumvalue selector 17, and performs multiplication P1 by t6=min(aq*Q2,ap*P2), and outputs the product T6′=P1*min(aq*Q2, ap*P2). Accordingly,the polynomial data T1, T2, T3, T4, T5′ and T6′ are outputted from thepolynomial calculator shown in FIG. 16, and these outputs of thepolynomial calculator are sent to the matrix calculator 4 or 4b.

Thus, according to the polynomial calculator 3 described with referenceto FIG. 19, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 1 in connection with Embodiment 1 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 19.

The difference between the number of calculation terms in the formula(9) and the number of calculation terms in FIG. 19 is that FIG. 19 showsa method of calculation for each pixel excluding data resulting in thecalculation terms which are of a value zero, while the formula (9)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (9) except the six calculation terms of m*y, b*r,b*r/(b+r), m*y/(m+y), min(m, hrm), and m*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at least two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel of the formula (9) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data. The combination ofeffective data is changed according to image data of the target pixel.For all image data, all the polynomial data can be effective.

FIGS. 20A to 20F schematically show relations between the six hues andfirst-order terms min(y, hry), min(y, hgy), min(c, hgc), min(c, hbc),min(m, hbm) and min(m, hrm), based on the comparison-result data. In thedrawings, broken lines a1 to a6 and b1 to b6 represent characteristicsobtained when the calculation coefficients aq1 to aq6 and ap1 to ap6 inhry, hrm, hgy, hgc, hbm and hbc are changed. Solid lines representcharacteristics obtained when the values of the calculation coefficientsaq1 to aq6 and ap1 to ap6 are 1. From FIGS. 20A to 207F, it can beunderstood that the first-order terms using comparison-result datacontribute to changes in the inter-hue areas of red-yellow,yellow-green, green-cyan, cyan-blue, blue-magenta, and magenta-red.

In other words, for example, for the inter-hue area of red-yellow, sincer=W, g=W/2 and b=0, with W being a constant, y=W, m=W/2, c=0, and min(y,hry)=W*W/2, and the other five terms are all zero.

Here, since the constant W represents a magnitude of a hue signal, asize of the constant W depends on color brightness or chroma of a pixel,and the first-order term min(r, hry) is a first-order function withrespect to the chroma. The other product terms are also first-orderfunctions with respect to the chroma in the inter-hue areas where theterms are effective. Accordingly, the effect on the color reproductiongiven by the first-order term based on each comparison-result data is afirst-order function with respect to the chroma. In other words, thefirst-order term based on each comparison-result data serves as afirst-order correction term for the chroma, in color reproduction.Accordingly, only min(y, hry) is an effective first-order term.Similarly, only min(y, hgy) is an effective term for yellow-green;min(c, hgc) for green-cyan; min(c, hbc) for cyan-blue; min(m, hbm) forblue-magenta; and min(m, hrm) for magenta-red.

The relationship between the six hues and second-order calculation termsy*hry, y*hgy, c*hgc, c*hbc, m*hbm, and m*hrm which are product termsbased on the comparison-result data and the hue data is identical tothat described with reference to FIGS. 17A to 17F in connection withEmbodiment 5 to Embodiment 8. Only y*hry is an effective second-ordercalculation term for red-yellow. Similarly, only y*hgy is an effectiveterm for yellow-green; c*hgc for green-cyan; c*hbc for cyan-blue; m*hbmfor blue-magenta; and m*hrm for magenta-red.

FIGS. 21A to 21B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3 are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order terms using comparison-result data based on the hue data,it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 9, the color conversion is performed onthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 9, hardware is used to performthe processing of the configuration of FIG. 16. Identical processing canbe performed by software, and an effect identical to that of Embodiment9 can be obtained.

Embodiment 10

According to the polynomial calculator 3 described with reference toFIG. 19 in connection with Embodiment 9, the formula used-fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 12 inconnection with Embodiment 2 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 19.

The difference between the number of calculation terms in the formula(10) and the number of calculation terms in FIG. 19 is that FIG. 19shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (10)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (10) except the six calculation terms of m*y, b*r,b*r/(b+r), m*y/(m+y), min(m, hrm), and m*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at last two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel of the formula (10) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data. The combination ofeffective data is changed according to image data of the target pixel.For all image data, all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (10) are identical to those of the formula (9) in Embodiment 9,and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 21A and21B. Accordingly, as in Embodiment 9, if the coefficient generatorchanges coefficients for a calculation term effective for a hue or aninter-hue area to be adjusted, only the target hue can be adjusted, andthe inter-hue areas can also be corrected. Further, if coefficientsgenerated by the calculation coefficient generator 15 in the polynomialcalculator 3 are changed, part of the inter-hue area where a calculationterm in the inter-hue area is effective can be changed without givingany influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order calculation terms using comparison-result data based on thehue data, it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 10, the color conversion is performed onthe complementary color data obtained by conversion from the input imagedata R, G, and B, so that it is possible to achieve good colorreproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 11

According to the polynomial calculator 3 described with reference toFIG. 19 in connection with Embodiment 9, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 13 in connection withEmbodiment 3 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(11) and the number of calculation terms in the polynomial calculator inFIG. 19 is that FIG. 19 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (11) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (11) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(m, hrm), m*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (11) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 11, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 12

According to the polynomial calculator 3 described with reference toFIG. 19 in connection with Embodiment 9, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 15 inconnection with Embodiment 4 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(12) and the number of calculation terms in the polynomial calculator inFIG. 19 is that FIG. 19 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (12) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (12) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(m, hrm), m*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (12) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 12, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 13

As another example, the polynomial calculator 3 may be formed as shownin FIG. 22, to calculate the polynomial data.

FIG. 22 is a block diagram showing another example of configuration ofthe polynomial calculator 3. In the drawing, reference numerals 11 to 17and 19 denote members identical to those of the polynomial calculatorshown in FIG. 2. Reference numeral 18b denotes a minimum value selectorfor selecting and outputting the minimum value of the input data.

Next, the operation of the polynomial calculator 3 shown in FIG. 22 willbe described. The operation of the zero remover 11, and the operationfor outputting T3=Q1*Q2, T4=T3/(Q1+Q2), T1=P1*P2 and T2=T1/(P1+P2) bythe multipliers 12a and 12b, the adders 13a and 13b and the dividers 14aand 14b, and the operation for outputting t6=min(aq*Q2, ap*P2) by thecalculation coefficient generator 15, the calculators 16a and 16b andthe minimum value selector 17 are identical to those of the embodimentdescribed above with reference to FIG. 2. Thus, detailed explanationthereof will be omitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 issupplied to the minimum value selector 18b and the multiplier 19. Theminimum value selector 18b also receives the output data P1 from thezero remover 11, and outputs the minimum value T5′=min(P1, min(aq*Q2,ap*P2) between P1 and t6=min(aq*Q2, ap*P2).

The multiplier 19 receives the data Q1 from the zero remover 11, and theoutput t6 from the minimum value selector 17, and performsmultiplication Q1 by t6=min(aq*Q2, ap*P2), and outputs the productT6=Q1*min(aq*Q2, ap*P2). Accordingly, the polynomial data T1, T2, T3,T4, T6 and T5′ are outputted from the polynomial calculator shown inFIG. 22, and these outputs of the polynomial calculator are sent to thematrix calculator 4 or 4b.

Thus, according to the polynomial calculator 3 described with referenceto FIG. 22, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 1 in connection with Embodiment 1 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 22.

The difference between the number of calculation terms in the formula(13) and the number of calculation terms in FIG. 22 is that FIG. 22shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (13)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations equations g=0 and c=0 hold hold. Accordingly, the twenty-fourcalculation terms in the formula (13) except the six calculation termsof m*y, b*r, b*r/(b+r), m*y/(m+y), min(m, hrm), and r*hrm, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fourcalculation terms minus the six calculation terms) are of a value zero.Accordingly, twenty-four polynomial data for one pixel of the formula(13) can be reduced to six effective data, and this reduction isachieved by exploiting a characteristic of the hue data. The combinationof effective data is changed according to image data of the targetpixel. For all image data, all the polynomial data can be effective.

The relations between the six hues and first-order terms min(y, hry),min(y, hgy), min(c, hgc), min(c, hbc), min(m, hbm) and min(m, hrm),based on the comparison-result data are identical to those describedwith reference to FIGS. 20A to 20F in connection with Embodiments 9 to12. The relations between the six hues and the second-order terms r*hry,g*hgy, g*hgc, b*hbc, b*hbm, and r*hrm which are product terms based onthe comparison-result data and the hue data are identical to thosedescribed with reference to FIGS. 10A to 10F in connection withEmbodiments 1 to 4. Accordingly, it can be understood that thefirst-order terms and second-order terms using comparison-result datacontribute to changes in the inter-hue areas of red-yellow,yellow-green, green-cyan, cyan-blue, blue-magenta, and magenta-red. Itis also understood that only min(y, hry) and r*hry are effectivefirst-order and second-orders terms for red-yellow; min(y, hgy) andg*hgy for yellow-green; min(c, hgc) and g*hgc for green-cyan; min(c,hbc) and b*hbc for cyan-blue; min(m, hbm) and b*hbm for blue-magenta;and min(m, hrm) and r*hrm for magenta-red.

FIGS. 23A and 23B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3 are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order terms using comparison-result data based on the hue data,it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 13, the color conversion is performed onthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 13, hardware is used to performthe processing of the configuration of FIG. 22. Identical processing canbe performed by software, and an effect identical to that of Embodiment13 can be obtained.

Embodiment 14

According to the polynomial calculator 3 described with reference toFIG. 22 in connection with Embodiment 13, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 12 inconnection with Embodiment 2 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 22.

The difference between the number of calculation terms in the formula(14) and the number of calculation terms in FIG. 22 is that FIG. 22shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (14)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α shown in FIG. 3 being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (14) except the six calculation terms of m*y, b*r,b*r/(b+r), m*y/(m+y), min(m, hrm), and r*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at least two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel of the formula (14) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data. The combination ofeffective data is changed according to image data of the target pixel.For all image data, all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (14) are identical to those of the formula (13) in Embodiment13, and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 23A and23B. Accordingly, as in Embodiment 13, if the coefficient generatorchanges coefficients for a calculation term effective for a hue or aninter-hue area to be adjusted, only the target hue can be adjusted, andthe inter-hue areas can also be corrected.

Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3 are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, itis possible to adjust only the target hue, among the six hues of red,blue, green, yellow, cyan and magenta, without affecting other hues.Moreover, by changing the coefficients relating the first-order andsecond-order calculation terms using comparison-result data based on thehue data, it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, the productterms and the second-order terms using comparison-result data representsecond-order calculations with respect to chroma, and the fraction termsand the first-order terms using comparison-result data representfirst-order calculations with respect to chroma. As a result, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 14, the color conversion is performed onthe complementary color data obtained by conversion from the input imagedata R, G, and B, so that it is possible to achieve good colorreproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 15

According to the polynomial calculator 3 described with reference toFIG. 22 in connection with Embodiment 13, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 13 in connection withEmbodiment 3 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(15) and the number of calculation terms in the polynomial calculator inFIG. 22 is that FIG. 22 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (15) represents a general formula for a set ofpixels. In other words, the six hue data have such a-characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (15) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(m, hrm), r*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (15) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and for instance, it is possible to selectamong the standard black, reddish black, bluish black, and the like.Accordingly, it is possible to obtain a color conversion device or colorconversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 15, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 16

According to the polynomial calculator 3 described with reference toFIG. 22 in connection with Embodiment 13, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 15 inconnection with Embodiment 4 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(16) and the number of calculation terms in the polynomial calculator inFIG. 22 is that FIG. 22 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (16) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown in FIG. 3 beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (16) except the sevencalculation terms of m*y, b*r, b*r/(b+r), m*y/(m+y), min(m, hrm), r*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (16) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the fraction terms relating to the specific hues, andthe coefficients of the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 16, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 17

FIG. 24 is a block diagram showing another example of configuration of acolor conversion device according to Embodiment 17 of the presentinvention. In the drawing, reference numerals 1, 2 and 6 denote membersidentical to those described with reference to FIG. 1 in connection withEmbodiment 1. Reference numeral 3b denotes a polynomial calculator; 4c,a matrix calculator; and 5c, a coefficient generator.

FIG. 25 is a block diagram showing an example of configuration of thepolynomial calculator 3b. In the drawing, reference numerals 11, 12a,12b and 15 to 19 denote members identical to those in the polynomialcalculator 3 described with reference to FIG. 2 in connection withEmbodiment 1. Reference numerals 30a and 30b denote minimum valueselectors for selecting and outputting minimum values of inputted data.

Next, the operation will be described. The operations of the minimum andmaximum calculator 1 and the hue data calculator 2 are identical to theoperations of those of Embodiment 1, so that detailed explanationthereof will be omitted. The polynomial calculator 3b selects thenon-zero data Q1 and Q2 among r, g and b, and non-zero data P1 and P2among y, m and c, in accordance with the identification code S1, andperforms calculation on the selected data. This will be explained withreference to FIG. 25.

In the polynomial calculator 3b, the inputted hue data, r, g, b, y, mand c and the identification code S1 are sent to the zero remover 11,which outputs, based on the identification code S1, two non-zero data Q1and Q2 among r, g and b and two non-zero data P1 and P2 among y, m andc. The data Q1 and Q2 outputted from the zero remover 11 are inputted tothe multiplier 12a, which determines and outputs the product T3=Q1*Q2.The data P1 and P2 outputted from the zero remover 11 are inputted tothe multiplier 12b, which determines and outputs the product T1=P1*P2 iscalculated and outputted. These operations are identical to those ofEmbodiment 1 described above with reference to FIG. 2. Also, theoperations of the calculation coefficient generator 15, the calculators16a and 16b, the minimum value selectors 17 and 18, and the multiplier19 are identical to those of Embodiment 1. Detailed explanation thereofwill therefore be omitted.

The data Q1 and Q2 outputted from the zero remover 11 are inputted tothe minimum value selector 30a, which selects the minimum valueT8=min(Q1, Q2). The data P1 and P2 outputted from the zero remover 11are inputted to the minimum value selector 30b, which selects andoutputs the minimum value T7=min(P1, P2). The above polynomial data T1,T3, T5, T6, T7, and T8 outputted from the polynomial calculator 3b, andthese outputs of the polynomial calculator 3b are sent to the matrixcalculator 4c.

The coefficient generator 5c shown in FIG. 24 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4c. The matrix calculator 4creceives the hue data r, g and b from the hue data calculator 2, thepolynomial data T1, T3, T5, T6, T7 and T8 from the polynomial calculator3b, and the coefficients U from the coefficient generator 5c, anddetermines the image data R, G, and B according to the followingformula: $\begin{matrix}{\begin{bmatrix}{R1} \\{G1} \\{B1}\end{bmatrix} = {{({Eij})\begin{bmatrix}r \\g \\b\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T7} \\{T3} \\{T8} \\{T5} \\{T6}\end{bmatrix}}}} & (38)\end{matrix}$

Here, with regard to (Eij), i=1 to 3, and j=1 to 3. With regard to(Fij), i=1 to 3, and j=1 to 6.

FIG. 26 is a block diagram showing a part of an example of configurationof the matrix calculator 4c, for calculating and outputting R1. In thedrawing, reference numerals 20a to 20b and 21a to 21f denote membersidentical to those shown in FIG. 5.

Next, the operation of the matrix calculator 4c shown in FIG. 26 will bedescribed. The multipliers 20a to 20g receive the hue data r, thepolynomial data T1, T3, T5, T6, T7 and T8 from the polynomial calculator3b, and the coefficients U (Eij) and U (Fij) from the coefficientgenerator 5c, and determine and output the respective products. Theadders 21a to 21c receive the products outputted from the multipliers20b to 20g, and add the respective input data, and output the respectivesums. The adder 21d adds the data from the adders 21a and 21b. The adder21e adds the data from the adders 21c and 21d. The adder 21f adds theoutput from the adder 21e and the output from the multiplier 20a, andoutputs the sum total thereof as image data R1. In the configuration ofFIG. 26, if the hue data r is substituted by g or b, image data G1 or B1can be calculated.

Those of the coefficients (Eij) and (Fij) which respectively correspondto the hue data r, g or b are used. If the configuration of FIG. 26 areprovided in parallel for the hue data r, g and b, high-speed matrixcalculation can be performed.

The synthesizer 6 receives the image data R1, G1 and B1 from the matrixcalculator 4c, and the minimum value α representing achromatic data,which is outputted from the minimum and maximum calculator 1, andperforms addition, and outputs the image data R, G and B. Thecalculation formula for determining the image data R, G and B obtainedby the color conversion device of FIG. 24 is given below:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 24.

The difference between the number of calculation terms in the formula(17) and the number of calculation terms in the polynomial calculator 3bin FIG. 24 is that FIG. 24 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (17) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as described in connection withEmbodiment 1, 3. For example, in the case where the value of theidentification code S1 is 0, with the maximum and minimum values β and αshown in FIG. 3 being respectively Ri and Gi, equations g=0 and c=0hold. Accordingly, the twenty-four calculation terms in the formula (17)except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(r, hrm) and r*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (17) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

FIGS. 27A to 27F schematically show relations between the six hue dataand the calculation terms min(m, y), min (r, g), min(y, c), min(g, b),min(c, m) and min(b, r) based on the comparison-result data. Eachcalculation term has a characteristic of a first-order term. Forexample, with W being a constant, since r=W and g=b=0 for red, y=m=W andc=0. In this case, min(m, y)=W, and the other five terms are zero. Thesize of the constant W depends on color brightness or chroma of a pixel.Since min (m, y)=W, an effect of min(m, y) on color reproduction is afirst-order function with regard to chroma. In other words, only min(m,y) is an effective first-order term for red. Similarly, the othercalculation terms using the comparison-result data are first-orderfunctions with regard to chroma for the hues for which the respectiveterms are effective. Only min(y, c) is an effective first-order term forgreen; min(c, m) for blue; min(g, b) for cyan; min(b, r) for magenta;and min(r, g) for yellow.

FIGS. 28A and 28B show relations between the six hues and the inter-hueareas, and those of the calculation terms obtained by the polynomialcalculator 3b shown in FIG. 24 which are effective for the respectivehues and inter-hue areas. Thus, if the coefficient generator 5c changescoefficients for calculation terms effective for a hue or an inter-huearea to be adjusted, only the target hue can be adjusted, and theinter-hue areas can also be corrected. Further, if coefficientsgenerated by the calculation coefficient generator 15 in the polynomialcalculator 3b are changed, part of the inter-hue area where acalculation term in the inter-hue area is effective can be changedwithout giving any influence to the other hues.

If the coefficients U (Eij) generated by the coefficient generator 5c inEmbodiment 17 are set as in formula (33) and the coefficients of U (Fij)are all set to zero, no color conversion is performed, as was describedin connection with Embodiment 1. If, among the coefficients U (Fij),those for the product terms and the calculation terms usingcomparison-result data which relate to the hues or inter-hue areas to bechanged are set to certain appropriate values, and the othercoefficients are set to zero, only the target hues or inter-hue areascan be adjusted. For example, coefficients for the first-order termmin(m, y) relating to red are set, the hue red is changed. For changinginter-hue area red-yellow, the coefficients for the first-order termmin(r, hry) and the coefficients for the second-order term r*hry areused.

The hues to which the first-order fraction terms T4=Q1*Q2/(Q1+Q2) andT2=P1*P2/(P1+P2) in Embodiments 1 to 16 relate and the hues to which thefirst-order terms T8=min(Q1, Q2) and T7=min(P1, P2) based on thecomparison-result data in Embodiment 17 are identical to one another.However, in the case of the calculation terms using comparison-resultdata in Embodiment 17, the first-order terms effective for a specifichue can be obtained just through selection of the minimum values of therespective hue data. Accordingly, processing can be simplified, and theprocessing speed can be increased, compared with the case in which thecalculation terms are obtained by multiplication and division.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficientsrelating the first-order and second-order terms relating to theinter-hue areas, it is possible to independently correct the inter-hueareas of red-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta,and magenta-red, to change the six inter-hue areas. Furthermore, theproduct terms and the second-order terms using comparison-result datarepresent second-order calculations with respect to chroma, and thefirst-order terms using comparison-result data represent first-ordercalculations with respect to chroma. As a result, by using both of thefirst-order and second-order terms, it is possible to correct thenon-linearity of image printing or the like with respect to chroma.Accordingly, it is possible to obtain a color conversion device or colorconversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 9, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In Embodiment 17 described above, the hue data r, g and b, y, m and c,and the maximum and minimum values β and α were calculated based on theinputted image data R, G and B so as to obtain the calculation terms forthe respective hues, and after the matrix calculation, the image-data R,G and B were obtained. However, after the outputted image data areobtained, the data R, G and B may be converted into complementary colordata C, M and Y. If the six hue data, the maximum value β and theminimum value α can be obtained, and the calculation terms shown in FIG.28 can be obtained, and the coefficients used in the matrix calculationcan be changed for the respective hues and inter-hue areas, the sameeffects will be realized.

In the above-description of Embodiment 17, hardware is used to performthe processing of the configuration of FIG. 24. Identical processing canbe performed by software, and an effect identical to that of Embodiment17 can be obtained.

Embodiment 18

In Embodiment 17, the hue data r, g and b, y, m and c, and the maximumand minimum values β and α were calculated based on the inputted imagedata R, G and B so as to obtain the calculation terms for the respectivehues, and after the matrix calculation, the image data R, G and B wereobtained. But the image data R, G and B may first be converted intocomplementary color data C, M and Y, and then color conversion-may beexecuted by inputting the complementary color data C, M and Y.

FIG. 29 is a block diagram showing an example of configuration of acolor conversion device of Embodiment 18 of the present invention. Inthe drawing, reference numerals 1b, 2b, 10 and 6 denote membersidentical to those described with reference to FIG. 12 in connectionwith Embodiment 2, and reference numerals 3b, 4c and 5c denote membersidentical to those described with reference to FIG. 24 in connectionwith Embodiment 17.

Next, the operation will be described. The complement calculator 10receives the image data R, G and B, and outputs complementary color dataCi, Mi and Yi obtained by determining 1's complements. The minimum andmaximum calculator 1b outputs the maximum and minimum values β and α ofeach of these complementary color data and an identification code S1 forindicating, among the six hue data, data which are zero.

Then, the hue data calculator 2b receives the the complementary colordata Ci, Mi and Yi and the maximum and minimum values β and α from theminimum and maximum calculator 1b, performs subtraction of r=β−Ci,g=β−Mi, b=β−Yi, y=Yi−α, m=Mi−α, and c=Ci−α, and outputs six hue data r,g, b, y, m and c. Here, at least two among these six hue data are zero.The identification code S1 outputted from the minimum and maximumcalculator 1b is used for specifying, among the six hue data, data whichis zero. The value of the identification code depends on which of Ci, Miand Yi the maximum and minimum values β and α are. Relations between thedata among the six hue data which are zero, and the values of theidentification code are the same as those in Embodiment 1, and thusfurther explanation will be omitted.

Then, the six hue data r, g, b, y, m and c outputted from the hue datacalculator 2 are sent to the polynomial calculator 3b, and the hue datac, m and y are also sent to the matrix calculator 4c. The polynomialcalculator 3b also receives the identification code S1 outputted fromthe minimum and maximum calculator 1, and performs calculation byselecting, from the hue data, two data Q1 and Q2 which are not zero, andfrom the hue data y, m and c, two data P1 and P2 which are not of avalue zero. The operations are similar to those described in connectionwith Embodiment 17 with reference to FIG. 25, and their details areomitted.

The outputs from the polynomial calculator 3b are sent to the matrixcalculator 4c. The coefficient generator 5c generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4c. Based on the hue data c, m andy from the hue data calculator 2b, polynomial data T1, T3, and T5 to T8from the polynomial calculator 3b and coefficients U from thecoefficient generator 5c, the matrix calculator 4c outputs the resultsof calculation according to the following formula (39), as image dataC1, M1 and Y1. $\begin{matrix}{\begin{bmatrix}{C1} \\{M1} \\{Y1}\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T7} \\{T3} \\{T8} \\{T5} \\{T6}\end{bmatrix}}}} & (39)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 6.

The operation at the matrix calculator 4c is similar to that describedwith reference to FIG. 26 in connection with Embodiment 17, but theinputted hue data is c (or m, y) and C1 (or M1, Y1) is calculated andoutputted. The detailed description thereof is therefore omitted.

The synthesizer 6 receives the image data C1, M1 and Y1 from the matrixcalculator 4c and the minimum value α outputted from the minimum andmaximum calculator 1b representing the achromatic data, performsaddition, and outputs image data C, M and Y. The formula used forobtaining the image data obtained by color conversion by thecolor-conversion device of FIG. 29 is therefore as follows:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 24.

The difference between the number of calculation terms in the formula(18) and the number of calculation terms in FIG. 29 is that FIG. 29shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (18)represents a general formula for a set of pixels. In other words, as inthe above-described embodiments, the six hue data have such acharacteristic that at least two of them are zero. For example, in thecase where the value of the identification code S1 is 0, with themaximum and minimum values β and α being respectively Ri and Gi,equations g=0 and c=0 hold. Accordingly, the twenty-four calculationterms in the formula (18) except the six calculation terms of m*y, b*r,min(b, r), min(m, y), min (r, hrm) and r*hrm, i.e., the eighteen dataare of a value zero. Similarly, in the case where the identificationcode is of the other values, since at least two data among the hue dataare of a value zero, the eighteen data (twenty-four calculation termsminus the six calculation terms) are of a value zero. Accordingly,twenty-four polynomial data for one pixel for the formula (18) can bereduced to six effective data, and this reduction is achieved byexploiting a characteristic of the hue data.

The combination of effective data changes depending on the image data ofthe target pixel (the pixel in question), and all the polynomial dataare effective in all the image data.

The calculation terms of the above formula (18) produced by thepolynomial calculator are identical to those of the formula (17)described in connection with Embodiment 17, and the relations betweenthe six hues and inter-hue areas, and the effective calculation termsare identical to those shown in FIGS. 28A and 28B. Accordingly, as inthe case of Embodiment 17, by changing coefficients of the effectivecalculation terms for hues or inter-hue areas to be adjusted in thecoefficient generator 5c, it is possible to adjust only the target huesor inter-hue area. Further, by changing coefficients generated by thecalculation coefficient generator 15 in the polynomial calculator 3b,the calculation terms effective in the areas can be changed withoutinfluencing the other hues.

If the coefficients U (Eij) generated by the coefficient generator 5c ofEmbodiment 17 are set as in the formula (33), and the coefficients U(Fij) are all set to zero, no color conversion is performed, as wasdescribed in connection with the above embodiments. By setting thosecoefficients U (Fij) for the product terms, and calculation terms basedon comparison-result data which relate to the hues or inter-hue areas tobe changed, and setting the other coefficients to zero, it is possibleto adjust only the particular hues or inter-hue areas.

For instance, if the coefficients relating to the first-ordercalculation term min(m, y) relating to red is set, the hue red ischanged. For changing the inter-hue area, the coefficients relating tothe first-order term min(r, hry) and the second-order term r*hry areused.

As apparent from the foregoing, by changing the coefficients of theproduct term and first-order calculation terms based on the comparisondata of the hue data, it is possible to adjust only the target hue amongthe six hues of red, blue, green, yellow, cyan and magenta, withoutaffecting other hues. By changing tie the coefficients for thefirst-order terms and second-order terms relating to inter-hue areas, itis possible to correct the six inter-hue areas of red-yellow,yellow-green, green-cyan, cyan-blue, blue-magenta, and magenta-redindependently. Moreover, by using both the second-order terms and thefirst-order terms, it is possible to correct the non-linearity of thechroma in image printing or the like. Accordingly, it is possible toobtain a color conversion device or color conversion method with whichthe conversion characteristics can be flexibly varied, and which doesnot require a large-capacity memory. In addition, in the Embodiment 2,the input image data R, G, and B are converted to complementary colordata C, M, and Y, and the color conversion is performed on thecomplementary color data C, M, and Y, so that it is possible to performgood color reproduction in of print data C, M, and Y in a printingdevice or the like.

In the above-description of Embodiment 18, hardware is used to performthe processing of the configuration shown in FIG. 29. Identicalprocessing can be performed by software in the color conversion device,and an effect identical to that of Embodiment 18 can be obtained.

Embodiment 19

In Embodiment 17, part of the matrix calculator 4c is assumed to be asshown in the block diagram of FIG. 26, to perform the calculationaccording to the formula (17). As an alternative, coefficients for theminimum value α which is achromatic data may be generated in thecoefficient generator, as shown in FIG. 30, to adjust the achromaticcomponent.

FIG. 30 is a block diagram showing an example of configuration of thecolor conversion device according to Embodiment 19. In the figure,reference numerals 1, 2 and 3b denote members identical to thosedescribed in connection with Embodiment 17 with reference to FIG. 24.Reference numeral 4d denotes a matrix calculator, and 5d denotes acoefficient generator.

The operation will next be described. The operations at the minimum andmaximum calculator 1 for determining the maximum value β, the minimumvalue α, and the identification code S1, based on the input data, at thehue data calculator 2 for determining the six hue data, and at thepolynomial calculator 3b for determining the calculation terms areidentical to those of Embodiment 17, so their details are omitted.

The coefficient generator 5d in FIG. 30 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4d. Based on the hue data r, g,and b from the hue data calculator 2, polynomial data T1, T3, and T5 toT8 from the polynomial calculator 3b, the minimum value from the minimumand maximum calculator 1, and coefficients U from the coefficientgenerator 5d, the matrix calculator 4d performs calculation inaccordance with the following formula (40) to adjust the achromaticcomponent. $\begin{matrix}{\begin{bmatrix}R \\G \\B\end{bmatrix} = {{({Eij})\begin{bmatrix}r \\g \\b\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T7} \\{T3} \\{T8} \\{T5} \\{T6} \\\alpha\end{bmatrix}}}} & (40)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 7.

FIG. 31, which is a block diagram, shows an example of configuration ofpart of the matrix calculator 4d. In FIG. 31, reference numerals 20a to20g, 21a to 21f denote members identical to those in the matrixcalculator 4c of Embodiment 17. Reference numerals 22 and 23 denotemembers identical to those in the matrix calculator 4b of Embodiment 3in FIG. 14.

Next, the operation of the matrix calculator 4d of FIG. 31 will bedescribed. The multipliers 20a to 20g receive the hue data r, thepolynomial data T1, T3, and T5 to T8 from the polynomial calculator 3band the coefficients U (Eij) and U (Fij) from the coefficient generator5d, and output the products thereof. The adders 21a and 21f add theproducts and/or sums. Their operations are identical to those in thematrix calculator in the above-described embodiments. The multiplier 22receives the minimum value α of the R, G, B, from the minimum andmaximum calculator 1, which corresponds to the achromatic component, andthe coefficients U (Fij) from the coefficient generator 5d, anddetermines the product thereof, which is sent to the adder 23, and addedto the output of the adder 21f. The total sum is outputted as output Rof the image data R.

In the example of configuration shown in FIG. 31, if the hue data r isreplaced by the hue data g or b, image data G or B can be calculated.

The part of the coefficients (Eij) and (Fij) corresponding to the huedata r, g and b are used. In other words, if three configuration, eachsimilar to that of FIG. 31, are used in parallel for the hue data r, gand b, matrix calculation can be performed at a higher speed.

Thus, the matrix calculator 4d performs calculation on the variouscalculation terms and the minimum value α which is the achromatic data,using coefficients, adding the result to the hue data, to produce imagedata R, G and B. The formula used for producing the image data is givenbelow:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 25.

The difference between the number of calculation terms in the formula(19) and the number of calculation terms in FIG. 30 is that FIG. 30shows a method of calculation for each pixel excluding data resulting inthe calculation terms in the polynomial calculator which are of a valuezero, while the formula (19) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (19) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(r, hrm), r*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minutes the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (19) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

If all the coefficients relating to the minimum value α are of a value“1,” the achromatic data is not converted, and will be a value identicalto that of the achromatic data in the input data. If the coefficients inthe matrix calculation are changed, it is possible to select reddishblack, blush black or the like, so that it is possible to adjust theachromatic component.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the first-order calculation terms using comparison-resultdata based on the hue data, and the first-order and second-order termsrelating to inter-hue areas, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 19, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

In Embodiment 19 described above, the hue data r, g and b, y, m and c,and the maximum and minimum values β and α were calculated based on theinputted image data R, G and B so as to obtain the calculation terms forthe respective hues, and after the matrix calculation, the image data R,G and B were obtained. However, after the outputted image data areobtained, the data R, G and B may be converted into complementary colordata C, M and Y. In this case, the same effects will be realized.

In the above-description of Embodiment 19, hardware is used to performthe required processing. Identical processing can be performed bysoftware, as was also stated in connection with the above embodiments,and an effect identical to that of Embodiment 19 can be obtained.

Embodiment 20

In Embodiment 18, the configuration is such that the hue data and thecalculation terms, and the minimum value α are added together, as shownin formula (18). As an alternative, coefficients for the minimum value αwhich is achromatic data may be generated in the coefficient generator,as shown in FIG. 32, to adjust the achromatic component.

FIG. 32 is a block diagram showing an example of configuration of thecolor conversion device according to Embodiment 20. In the figure,reference numerals 10, 1b, 2b and 3b denote members identical to thoseof Embodiment 18 shown in FIG. 29, while reference numerals 4d and 5ddenote members identical to those of Embodiment 19 shown in FIG. 30.

The operation will next be described. The image data R, G and B areinputted to the complement calculator 10, which produces thecomplementary color data Ci, Mi and Yi by determining 1's complements.The minimum and maximum calculator 1b determines the maximum value β,the minimum value α, and the identification code S1, while the hue datacalculator 2b determines the six hue data. The polynomial calculator 3bdetermines the calculation terms. These operations are identical tothose of Embodiment 18 with regard to the complementary color data C, Mand Y, so their details are omitted.

The coefficient generator 5d in FIG. 32 generates calculationcoefficients U (Fij) and fixed coefficients U (Eij) for the polynomialdata based on the identification code S1, and sends the generatedcoefficients to the matrix calculator 4d. Based on the hue data c, m,and y from the hue data calculator 2b, polynomial data T1, T3, and T5 toT8 from the polynomial calculator 3b the minimum value from the minimumand maximum calculator 1b, and coefficients U from the coefficientgenerator 5d, the matrix calculator 4d performs calculation inaccordance with the following formula (41) to adjust the achromaticcomponent. $\begin{matrix}{\begin{bmatrix}C \\M \\Y\end{bmatrix} = {{({Eij})\begin{bmatrix}c \\m \\y\end{bmatrix}} + {({Fij})\begin{bmatrix}{T1} \\{T7} \\{T3} \\{T8} \\{T5} \\{T6} \\\alpha\end{bmatrix}}}} & (41)\end{matrix}$

For (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1 to 7.

The operation of the matrix calculator 4d is similar to that describedwith reference to FIG. 31 in connection with Embodiment 19, with theinputted hue data c (or m or y) being substituted to determine andoutput C (or M or Y), so that its detailed description is omitted.

Thus, the matrix calculator 4d performs calculation on the variouscalculation terms and the minimum value α which is the achromatic data,using coefficients, adding the result to the hue data, to produce imagedata C, M, and Y. The formula used for producing the image data is givenbelow:

Here, for (Eij), i=1 to 3 and j=1 to 3, and for (Fij), i=1 to 3 and j=1to 25.

As in the above-described embodiments, the difference between-the numberof calculation terms in the formula (20) and the number of calculationterms in FIG. 32 is that FIG. 32 shows a method of calculation for eachpixel excluding data resulting in the calculation terms in thepolynomial calculator which are of a value zero, while the formula (20)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-five calculation terms in the formula(20) except the seven calculation terms of m*y, b*r, min(b, r), min(m,y), min(r, hrm), r*hrm, and α, i.e., the eighteen data are of a valuezero. Similarly, in the case where the identification code is of theother values, since at least two data among the hue data are of a valuezero, the eighteen data (twenty-five calculation terms minus the sevencalculation terms) are of a value zero. Accordingly, twenty-fivepolynomial data for one pixel of the formula (20) can be reduced toseven effective data, and this reduction is achieved by exploiting acharacteristic of the hue data.

The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

If all the coefficients relating to the minimum value α are of a value“1,” the achromatic data is not converted, and will be a value identicalto that of the achromatic data in the input data. If the coefficients inthe matrix calculation are changed, it is possible to select reddishblack, bluish black or the like, so that it is possible to adjust theachromatic component.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the first-order terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity ofimaging printing or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 20, the color conversion is performed on thecomplementary color data C, M, and Y, having been obtained by conversionfrom the input image data R, G, and B, so that it is possible to achievegood color reproduction in color conversion of the printing data C, M,and Y in a printing device or the like, and greater advantages can beobtained.

In the above-description of Embodiment 204, hardware is used to performthe required processing. Identical processing can be performed bysoftware, as was also stated in connection with the above-describedembodiments, and an effect identical to that of Embodiment 20 can beobtained.

Embodiment 21

In Embodiments 17 to 20 described above, an example of the polynomialcalculator 3b shown in FIG. 25 was used, and the polynomial data arecalculated and outputted. As an alternative, a configuration shown inFIG. 33 may be used to calculate polynomial data.

FIG. 33 is a block diagram showing another example of configuration ofthe polynomial calculator 3b. In the drawing, reference numerals 11,12a, 12b, 15 to 18, 30a, and 30b denote members identical to those ofthe polynomial calculator of Embodiment 17 shown in FIG. 25. Referencenumeral 19b denotes a multiplier identical to that of Embodiment 5 shownin FIG. 16.

Next, the operation of the polynomial calculator 3b shown in FIG. 33will be described. The operation of the zero remover 11, the operationfor outputting T3=Q1*Q2 and T1=P1*P2 by means of the multipliers 12a and12b, the operation for outputting T8=min(Q1, Q2), T7=min(P1, P2), bymeans of the minimum value selectors 30a and 300b, and the operation foroutputting t6=min(aq*Q2, ap*P2) by means of the calculation coefficientgenerator 15, the calculators 16a and 16b and the minimum value selector17, and the operation for outputting the minimum values T5=min(Q1,min(aq*Q2, ap*P2)) between Q1 and t6 by means of the minimum valueselector 18 are identical to those of Embodiment 17 described above withreference to FIG. 25. Thus, detailed explanation thereof will beomitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 isalso supplied to the multiplier 19b, which also receives the data P1from the zero remover 11, and performs multiplication P1 byt6=min(aq*Q2, ap*P2), and outputs the product T6′=P1*min(aq*Q2, ap*P2).Accordingly, the polynomial data T1, T3, T5, T7, T8 and T6′ areoutputted from the polynomial calculator shown in FIG. 33, and theseoutputs of the polynomial calculator are sent to the matrix calculator4c or 4d.

Thus, according to the polynomial calculator 3b described with referenceto FIG. 33, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 1 in connection with Embodiment 1 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator shown in FIG. 33.

The difference between the number of calculation terms in the formula(21) and the number of calculation terms in FIG. 33 is that FIG. 33shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (21)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-four calculation terms in the formula(21) except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(r, hrm), and m*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (21) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristics of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The relations between the six hues and the second-order calculationterms y*hry, y*hgy, c*hgc, c*hbc, m*hbm, and m*hrm, which are productterms based on the comparison-result data and the hue data are identicalto those shown in FIGS. 17A to 17F. Only y*hry is an effectivesecond-order term for red-yellow. Similarly, only y*hgy is an effectiveterm for yellow-green; c*hgc for green-cyan; c*hbc for cyan-blue; m*hbmfor blue-magenta; and m*hrm for magenta-red.

FIGS. 34A and 34B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3b are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the first-order terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficientsrelating the first-order and second-order terms relating to theinter-hue areas, it is possible to independently correct the inter-hueareas of red-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta,and magenta-red, to change the six inter-hue areas. By using both of thefirst-order and second-order terms, it is possible to correct thenon-linearity of image printing or the like with respect to chroma.Accordingly, it is possible to obtain a color conversion device or colorconversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 21, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 21, hardware is used to performthe processing of the configuration of FIG. 33. Identical processing canbe performed by software, and an effect identical to that of Embodiment21 can be obtained.

Embodiment 22

According to the polynomial calculator 3b described with reference toFIG. 33 in connection with Embodiment 21, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 29 inconnection with Embodiment 18 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 33.

The difference between the number of calculation terms in the formula(22) and the number of calculation terms in FIG. 33 is that FIG. 33shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (22)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-four calculation terms in the formula(22) except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(r, hrm), and m*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (22) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (22) are identical to those of the formula (21) in Embodiment21, and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 34A and34B. Accordingly, if the coefficient generator changes coefficients fora calculation term effective for a hue or an inter-hue area to beadjusted, only the target hue can be adjusted, and the inter-hue areascan also be corrected. Further, if coefficients generated by thecalculation coefficient generator 15 in the polynomial calculator 3b arechanged, part of the inter-hue area where a calculation term in theinter-hue area is effective can be changed without giving any influenceto the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficientsrelating the first-order and second-order terms, it is possible toindependently correct the inter-hue areas of red-yellow, yellow-green,green-cyan, cyan-blue, blue-magenta, and magenta-red, to change the sixinter-hue areas. Furthermore, by using both of the first-order andsecond-order calculation terms, it is possible to correct thenon-linearity of image printing or the like with respect to chroma.Accordingly, it is possible to obtain a color conversion device or colorconversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 22, the color conversion is performed on thecomplementary color data obtained by conversion from the input imagedata R, G, and B, so that it is possible to achieve good colorreproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 23

According to the polynomial calculator 3b described with reference toFIG. 33 in connection with Embodiment 21, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 30 in connection withEmbodiment 19 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(23) and the number of calculation terms in the polynomial calculator inFIG. 33 is that FIG. 33 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (23) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (23) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(r, hrm), m*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minus the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (23) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data. Thecombination of effective data is changed according to image data of thetarget pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 23, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 24

According to the polynomial calculator 3b described with reference toFIG. 33 in connection with Embodiment 21, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 32 inconnection with Embodiment 20 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(24) and the number of calculation terms in the polynomial calculator inFIG. 33 is that FIG. 33 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (24) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α shown beingrespectively Ri and Gi, equations g=0 and c=0 hold. Accordingly, thetwenty-five calculation terms in the formula (24) except the sevencalculation terms of m*y, b*r, min(b, r), min(m, y), min(r, hrm), m*hrm,and α, i.e., the eighteen data are of a value zero. Similarly, in thecase where the identification code is of the other values, since atleast two data among the hue data are of a value zero, the eighteen data(twenty-five calculation terms minus the seven calculation terms) are ofa value zero. Accordingly, twenty-five polynomial data for one pixel ofthe formula (24) can be reduced to seven effective data, and thisreduction is achieved by exploiting a characteristic of the hue data.The combination of effective data is changed according to image data ofthe target pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 24, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 25

As another example, the polynomial calculator 3b may be formed as shownin FIG. 35, to calculate the polynomial data.

FIG. 35 is a block diagram showing another example of configuration ofthe polynomial calculator 3b. In the drawing, reference numerals 11,12a, 12b, 15 to 17, 30a, and 30b denote members identical to those ofthe polynomial calculator of Embodiment 17 shown in FIG. 25. Referencenumerals 18b and 19b denotes members identical to those of Embodiment 9shown in FIG. 19.

Next, the operation of the polynomial calculator 3b shown in FIG. 35will be described. The operation of the zero remover 11, and theoperation for outputting T3=Q1*Q2, and T1=P1*P2 by means of themultipliers 12a and 12b, the operation for outputting T8=min(Q1, Q2),and T7=min(P1, P2) by means of the minimum value selectors 30a and 30b,and the operation for outputting t6=min(aq*Q2, ap*P2) by means of thecalculation coefficient generator 15, the calculators 16a and 16b andthe minimum value selector 17 are identical to those of Embodiment 17described above with reference to FIG. 25. Thus, detailed explanationthereof will be omitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 issupplied to the minimum value selector 18b and the multiplier 19b. Theminimum value selector 18b also receives the output data P1 from thezero remover 11, and outputs the minimum value T5′=min(P1, min(aq*Q2,ap*P2) between P1 and t6=min(aq*Q2, ap*P2). The multiplier 19b receivesthe data P1 from the zero remover 11, and the output t6 from the minimumvalue selector 17, and performs multiplication P1 by t6=min(aq*Q2,ap*P2), and outputs the product T6′=P1*min(aq*Q2, ap*P2). Accordingly,the polynomial data T1, T3, T7, T8, T5′ and T6′ are outputted from thepolynomial calculator shown in FIG. 35, and these outputs of thepolynomial calculator are sent to the matrix calculator 4c or 4d.

Thus, according to the polynomial calculator 3b described with referenceto FIG. 35, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 24 in connection with Embodiment 17 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 35.

The difference between the number of calculation terms in the formula(25) and the number of calculation terms in FIG. 35 is that FIG. 35shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (25)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-four calculation terms in the formula(25) except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(m, hrm), and m*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (25) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The relations between the six hues and the first-order calculation termsmin(y, hry), min(y, hgy), min(c, hgc), min(c, hbc), min(m, hbm) andmin(m, hrm), based on the comparison-result data are identical to thoseshown in FIGS. 20A to 20F.

For red-yellow, only min(y, hry) is an effective first-order term.Similarly, only min(y, hgy) is an effective term for yellow-green;min(c, hgc) for green-cyan; min(c, hbc) for cyan-blue; min(m, hbm) forblue-magenta; and min(m, hrm) for magenta-red.

The relationship between the six hues and second-order calculation termsy*hry, y*hgy, c*hgc, c*hbc, m*hbm, and m*hrm which are product termsbased on the comparison-result data and the hue data is identical tothat described with reference to FIGS. 17A to 17F. Only y*hry is aneffective second-order calculation term for red-yellow. Similarly, onlyy*hgy is an effective term for yellow-green; c*hgc for green-cyan; c*hbcfor cyan-blue; m*hbm for blue-magenta; and m*hrm for magenta-red.

FIGS. 31A and 31B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3b are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficientsrelating the first-order and second-order terms relating to theinter-hue areas it is possible to independently correct the inter-hueareas of red-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta,and magenta-red, to change the six inter-hue areas. Furthermore, byusing both of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 9, the color conversion is performed onthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 25, hardware is used to performthe processing of the configuration of FIG. 35. Identical processing canbe performed by software, and an effect identical to that of Embodiment25 can be obtained.

Embodiment 26

According to the polynomial calculator 3b described with reference toFIG. 35 in connection with Embodiment 25, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 29 inconnection with Embodiment 18 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 35.

The difference between the number of calculation terms in the formula(26) and the number of calculation terms in FIG. 35 is that FIG. 35shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (26)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-four calculation terms in the formula(26) except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(m, hrm), and m*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (26) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (26) are identical to those of the formula (25) in Embodiment25, and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 36A and36B. Accordingly, if the coefficient generator changes coefficients fora calculation term effective for a hue or an inter-hue area to beadjusted, only the target hue can be adjusted, and the inter-hue areascan also be corrected. Further, if coefficients generated by thecalculation coefficient generator 15 in the polynomial calculator 3b arechanged, part of the inter-hue area where a calculation term in theinter-hue area is effective can be changed without giving any influenceto the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficientsrelating to the first-order and second-order terms relating to theinter-hue areas, it is possible to independently correct the inter-hueareas of red-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta,and magenta-red, to change the six inter-hue areas. Furthermore, byusing both of the second-order and first-order calculation terms, it ispossible to correct the non-linearity of image printing or the like withrespect to chroma. Accordingly, it is possible to obtain a colorconversion device or color conversion method with which the conversioncharacteristics can be changed flexibly, and which does not require alarge-capacity memory. In addition, in the Embodiment 10, the colorconversion is performed on the complementary color data obtained byconversion from the input image data R, G, and B, so that it is possibleto achieve good color reproduction in color conversion of printing dataC, M and Y in a printing device or the like, and greater advantages canbe obtained.

Embodiment 27

According to the polynomial calculator 3b described with reference toFIG. 35 in connection with Embodiment 25, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 30 in connection withEmbodiment 19 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(27) and the number of calculation terms in the polynomial calculator inFIG. 35 is that FIG. 3519 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (27) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (27) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(m, hrm), m*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minus the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (27) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data. Thecombination of effective data is changed according to image data of thetarget pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 27, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 28

According to the polynomial calculator 3b described with reference toFIG. 35 in connection with Embodiment 25, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 32 inconnection with Embodiment 20 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(28) and the number of calculation terms in the polynomial calculator inFIG. 35 is that FIG. 35 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (28) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (28) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(m, hrm), m*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minus the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (28) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data. Thecombination of effective data is changed according to image data of thetarget pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 28, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 29

As another example, the polynomial calculator 3b may be formed as shownin FIG. 37, to calculate the polynomial data.

FIG. 37 is a block diagram showing another example of configuration ofthe polynomial calculator 3b. In the drawing, reference numerals 11,12a, 12b, 15 to 17, 19, 30a and 30b denote members identical to those ofthe polynomial calculator of Embodiment 17 shown in FIG. 25. Referencenumeral 18b denotes a member identical to that of Embodiment 13 shown inFIG. 22.

Next, the operation of the polynomial calculator 3b shown in FIG. 37will be described. The operation of the zero remover 11 for outputtingT3=Q1*Q2, and T1=P1*P2, the operation of the minimum value selectors 30aand 30b for outputting T8=min(Q1, Q2), and T7=min(P1, P2), and theoperation for outputting t6=min(aq*Q2, ap*P2) by means of thecalculation coefficient generator 15, the calculators 16a and 16b andthe minimum value selector 17 are identical to those of Embodiment 17described with reference to FIG. 25. Thus, detailed explanation thereofwill be omitted.

The output t6=min(aq*Q2, ap*P2) from the minimum value selector 17 issupplied to the minimum value selector 18b and the multiplier 19. Theminimum value selector 18b also receives the output data P1 from thezero remover 11, and outputs the minimum value T5′=min(P1, min(aq*Q2,ap*P2) between P1 and t6=min(aq*Q2, ap*P2).

The multiplier 19 receives the data Q1 from the zero remover 11, and theoutput t6 from the minimum value selector 17, and performsmultiplication Q1 by t6=min(aq*Q2, ap*P2), and outputs the productT6=Q1*min(aq*Q2, ap*P2). Accordingly, the polynomial data T1, T3, T7,T8, T6 and T5′ are outputted from the polynomial calculator shown inFIG. 37, and these outputs of the polynomial calculator are sent to thematrix calculator 4c or 4d.

Thus, according to the polynomial calculator 3b described with referenceto FIG. 37, the formula used for determining the image data R, G and Bobtained by color conversion by the method described with reference toFIG. 24 in connection with Embodiment 17 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 37.

The difference between the number of calculation terms in the formula(29) and the number of calculation terms in FIG. 37 is that FIG. 37shows a method of calculation for each pixel excluding data resulting inthe calculation terms which are of a value zero, while the formula (29)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations equationsg=0 and c=0 hold hold. Accordingly, the twenty-four calculation terms inthe formula (29) except the six calculation terms of m*y, b*r, min(b,r), min(m, y), min(m, hrm), and r*hrm, i.e., the eighteen data are of avalue zero. Similarly, in the case where the identification code is ofthe other values, since at least two data among the hue data are of avalue zero, the eighteen data (twenty-four calculation terms minus thesix calculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (29) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The relations between the six hues and first-order terms min(y, hry),min(y, hgy), min(c, hgc), min(c, hbc), min(m, hbm) and min(m, hrm),based on the comparison-result data are identical to those describedwith reference to FIGS. 20A to 20F. The relations between the six huesand the second-order terms r*hry, g*hgy, g*hgc, b*hbc, b*hbm, and r*hrmwhich are product terms based on the comparison-result data and the huedata are identical to those described with reference to FIGS. 10A to10F. Accordingly, it can be understood that the first-order terms andsecond-order terms using comparison-result data contribute to changes inthe inter-hue areas of red-yellow, yellow-green, green-cyan, cyan-blue,blue-magenta, and magenta-red. It is also understood that only min(y,hry) and r*hry are effective first-order and second-orders terms forred-yellow; min(y, hgy) and g*hgy for yellow-green; min (c, hgc) andg*hbc for green-cyan; min(c, hbc) and b*hbc for cyan-blue; min(m, hbm)and b*hbm for blue-magenta; and min(m, hrm) and r*hrm for magenta-red.

FIGS. 38A and 38B respectively show relations between the six hues andinter-hue areas and effective calculation terms. Thus, if thecoefficient generator changes coefficients for a calculation termeffective for a hue or an inter-hue area to be adjusted, only the targethue can be adjusted, and the inter-hue areas can also be corrected.Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3b are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficients forthe first-order and second-order terms relating to the inter-hue areas,it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, by usingboth of the first-order and second-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 13, the color conversion is performed onthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device, such a monitor, or an imageprocessing device using image data represented by R, G, and B, andgreater advantages can be obtained.

In the above-description of Embodiment 29, hardware is used to performthe processing of the configuration of FIG. 37. Identical processing canbe performed by software, and an effect identical to that of Embodiment29 can be obtained.

Embodiment 30

According to the polynomial calculator 3b described with reference toFIG. 37 in connection with Embodiment 29, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 29 inconnection with Embodiment 18 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 24, andhry=min(aq1*g, ap1*m),hrm=min(aq2*b, ap2*y),hgy=min(aq3*r, ap3*c),hgc=min(aq4*b, ap4*y),hbm=min(aq5*r, ap5*c), andhbc=min(aq6*g, ap6*m), andaq1 to aq6 and ap1 to ap6 indicate calculation coefficients generated bythe calculation coefficient generator 15 shown in FIG. 37.

The difference between the number of calculation terms in the formula(30) and the number of calculation terms in FIG. 37 is that FIG. 37shows a method of calculation for each pixel excluding data resulting inthe calculation terms which area of a value zero, while the formula (30)represents a general formula for a set of pixels. In other words, thesix hue data have such a characteristic that at least two of them arezero, as in the above-described embodiments. For example, in the casewhere the value of the identification code S1 is 0, with the maximum andminimum values β and α being respectively Ri and Gi, equations g=0 andc=0 hold. Accordingly, the twenty-four calculation terms in the formula(30) except the six calculation terms of m*y, b*r, min(b, r), min(m, y),min(m, hrm), and r*hrm, i.e., the eighteen data are of a value zero.Similarly, in the case where the identification code is of the othervalues, since at least two data among the hue data are of a value zero,the eighteen data (twenty-four calculation terms minus the sixcalculation terms) are of a value zero. Accordingly, twenty-fourpolynomial data for one pixel of the formula (30) can be reduced to sixeffective data, and this reduction is achieved by exploiting acharacteristic of the hue data. The combination of effective data ischanged according to image data of the target pixel. For all image data,all the polynomial data can be effective.

The calculation terms by the polynomial calculator according to theformula (30) are identical to those of the formula (13) in Embodiment29, and the relations between the six hues and inter-hue areas, and theeffective calculation terms is identical to those shown in FIGS. 38A and38B. Accordingly, if the coefficient generator changes coefficients fora calculation term effective for a hue or an inter-hue area to beadjusted, only the target hue can be adjusted, and the inter-hue areascan also be corrected.

Further, if coefficients generated by the calculation coefficientgenerator 15 in the polynomial calculator 3b are changed, part of theinter-hue area where a calculation term in the inter-hue area iseffective can be changed without giving any influence to the other hues.

As apparent from the foregoing, by changing the coefficients of theproduct terms and the calculation terms using comparison-result databased on the hue data, it is possible to adjust only the target hue,among the six hues of red, blue, green, yellow, cyan and magenta,without affecting other hues. Moreover, by changing the coefficients forthe first-order and second-order terms relating to the inter-hue areas,it is possible to independently correct the inter-hue areas ofred-yellow, yellow-green, green-cyan, cyan-blue, blue-magenta, andmagenta-red, to change the six inter-hue areas. Furthermore, by usingboth of the second-order and first-order terms, it is possible tocorrect the non-linearity of image printing or the like with respect tochroma. Accordingly, it is possible to obtain a color conversion deviceor color conversion method with which the conversion characteristics canbe changed flexibly, and which does not require a large-capacity memory.In addition, in the Embodiment 30, the color conversion is performed onthe complementary color data obtained by conversion from the input imagedata R, G, and B, so that it is possible to achieve good colorreproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

Embodiment 31

According to the polynomial calculator 3b described with reference toFIG. 37 in connection with Embodiment 29, the formula used fordetermining the image data R, G and B obtained by color conversion bythe method described with reference to FIG. 30 in connection withEmbodiment 19 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(31) and the number of calculation terms in the polynomial calculator inFIG. 37 is that FIG. 37 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (31) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (31) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(m, hrm), r*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minus the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (31) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data. Thecombination of effective data is changed according to image data of thetarget pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 31, the color conversion is performed on theinput image data R, G, and B, so that it is possible to achieve goodcolor reproduction in a display device such as a monitor, or an imageprocessing device using image data represented by R, G and B, andgreater advantages can be obtained.

Embodiment 32

According to the polynomial calculator 3b described with reference toFIG. 37 in connection with Embodiment 29, the formula used fordetermining the complementary color data C, M and Y obtained by colorconversion by the method described with reference to FIG. 32 inconnection with Embodiment 20 will be as follows:

Here, for (Eij), i=1 to 3, and j=1 to 3, and for (Fij), i=1 to 3, andj=1 to 25.

The difference between the number of calculation terms in the formula(32) and the number of calculation terms in the polynomial calculator inFIG. 37 is that FIG. 37 shows a method of calculation for each pixelexcluding data resulting in the calculation terms which are of a valuezero, while the formula (32) represents a general formula for a set ofpixels. In other words, the six hue data have such a characteristic thatat least two of them are zero, as in the above-described embodiments.For example, in the case where the value of the identification code S1is 0, with the maximum and minimum values β and α being respectively Riand Gi, equations g=0 and c=0 hold. Accordingly, the twenty-fivecalculation terms in the formula (32) except the seven calculation termsof m*y, b*r, min(b, r), min(m, y), min(m, hrm), r*hrm, and α, i.e., theeighteen data are of a value zero. Similarly, in the case where theidentification code is of the other values, since at least two dataamong the hue data are of a value zero, the eighteen data (twenty-fivecalculation terms minus the seven calculation terms) are of a valuezero. Accordingly, twenty-five polynomial data for one pixel of theformula (32) can be reduced to seven effective data, and this reductionis achieved by exploiting a characteristic of the hue data. Thecombination of effective data is changed according to image data of thetarget pixel. For all image data, all the polynomial data can beeffective.

As apparent from the foregoing, by changing the coefficients of theproduct terms, the calculation terms using comparison-result data basedon the hue data, and the first-order and second-order terms relating tothe specific inter-hue area, it is possible to adjust only the targethue, or inter-hue area among the six hues of red, blue, green, yellow,cyan and magenta, and inter-hue areas, without affecting other hues, andother inter-hue areas. By using both of the first-order and second-ordercalculation terms, it is possible to correct the non-linearity of imageprinting or the like with respect to chroma. By changing thecoefficients relating to the minimum value α which is the achromaticdata, it is possible to adjust only the achromatic component, withoutaffecting the hue components, and, for instance, it is possible toselect among the standard black, reddish black, bluish black, and thelike. Accordingly, it is possible to obtain a color conversion device orcolor conversion method with which the conversion characteristics can bechanged flexibly, and which does not require a large-capacity memory. Inaddition, in the Embodiment 32, the color conversion is performed on thecomplementary color data C, M and Y obtained by color conversion fromthe input image data R, G, and B, so that it is possible to achieve goodcolor reproduction in color conversion of printing data C, M and Y in aprinting device or the like, and greater advantages can be obtained.

1. A color conversion device for converting first color data to secondcolor data comprising: a first calculator for generating a plurality ofhue data representing achromatic chroma components of a first colordata; a code generator for generating an identification code thatindicates a hue of the first color data; a selector for selecting thehue data according to the identification code; a second calculator forgenerating calculation terms, each of which is effective for a specifichue, based on the selected hue data; a coefficient generator forproviding matrix coefficients based on the identification code; and amatrix calculator that performs matrix calculation using the calculationterms and the matrix coefficients to produce the second color data. 2.The color conversion device according to claim 1, further comprising: aminimum and maximum calculator for determining a minimum value and amaximum value of the first color data, wherein the code generatorgenerates the identification code, based on the minimum value and themaximum value.
 3. A color conversion method for converting first colordata to second color data, the method comprising: generating a pluralityof hue data representing achromatic chroma components of the first colordata; generating, utilizing a code generator, an identification codethat indicates a hue of the first color data; selecting the hue dataaccording to the identification code; generating calculation terms, eachof which is effective for a specific hue, based on the selected huedata; providing matrix coefficients based on the identification code;and performing, utilizing a matrix calculator, matrix calculation usingthe calculation term and the matrix coefficients to produce the secondcolor data.
 4. The color conversion method according to claim 3, furthercomprising: determining a minimum value and a maximum value of the firstcolor data, wherein the identification code is generated based on theminimum value and the maximum value.